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1.
Methods Inf Med ; 2022 Jan 06.
Artículo en Inglés | MEDLINE | ID: mdl-34991173

RESUMEN

OBJECTIVE: Natural language processing (NLP) systems convert unstructured text into analyzable data. Here, we describe the performance measures of NLP to capture granular details on nodules from thyroid ultrasound (US) reports and reveal critical issues with reporting language. METHODS: We iteratively developed NLP tools using clinical Text Analysis and Knowledge Extraction System (cTAKES) and thyroid US reports from 2007 to 2013. We incorporated nine nodule features for NLP extraction. Next, we evaluated the precision, recall, and accuracy of our NLP tools using a separate set of US reports from an academic medical center (A) and a regional health care system (B) during the same period. Two physicians manually annotated each test-set report. A third physician then adjudicated discrepancies. The adjudicated "gold standard" was then used to evaluate NLP performance on the test-set. RESULTS: A total of 243 thyroid US reports contained 6,405 data elements. Inter-annotator agreement for all elements was 91.3%. Compared with the gold standard, overall recall of the NLP tool was 90%. NLP recall for thyroid lobe or isthmus characteristics was: laterality 96% and size 95%. NLP accuracy for nodule characteristics was: laterality 92%, size 92%, calcifications 76%, vascularity 65%, echogenicity 62%, contents 76%, and borders 40%. NLP recall for presence or absence of lymphadenopathy was 61%. Reporting style accounted for 18% errors. For example, the word "heterogeneous" interchangeably referred to nodule contents or echogenicity. While nodule dimensions and laterality were often described, US reports only described contents, echogenicity, vascularity, calcifications, borders, and lymphadenopathy, 46, 41, 17, 15, 9, and 41% of the time, respectively. Most nodule characteristics were equally likely to be described at hospital A compared with hospital B. CONCLUSIONS: NLP can automate extraction of critical information from thyroid US reports. However, ambiguous and incomplete reporting language hinders performance of NLP systems regardless of institutional setting. Standardized or synoptic thyroid US reports could improve NLP performance.

2.
Int J Stroke ; : 17474930211066427, 2022 Jan 05.
Artículo en Inglés | MEDLINE | ID: mdl-34983259

RESUMEN

Intracranial atherosclerotic disease is one of the leading causes of ischemic strokes and poses a moderate risk of recurrence. Diagnosis is currently limited to stenosis on luminal imaging, which likely underestimates the true prevalence of the disease. Detection of non-stenosing intracranial atherosclerosis is important in order to optimize secondary stroke prevention strategies. This review collates findings from the early seminal trials and the latest studies in advanced radiological techniques that characterize symptomatic intracranial atherosclerotic disease across various imaging modalities. While computed tomography angiography (CTA) and magnetic resonance angiography (MRA) comprise diagnostic mainstays in identifying stenotic changes secondary to atherosclerosis, emerging techniques such as high-resolution MRA, quantitative MRA, and computational fluid dynamics may reveal a myriad of other underlying pathophysiological mechanisms.

3.
Environ Pollut ; 295: 118667, 2022 Feb 15.
Artículo en Inglés | MEDLINE | ID: mdl-34896397

RESUMEN

Current approaches in chemical hazard assessment face significant challenges because they rely on live animal testing, which is time-consuming, expensive, and ethically questionable. These concerns serve as an impetus to develop new approach methodologies (NAMs) that do not rely on live animal tests. This study explored a molecular benchmark dose (BMD) approach using a 7-day embryo-larval fathead minnow (FHM) assay to derive transcriptomic points-of-departure (tPODs) to predict apical BMDs of fluoxetine (FLX), a highly prescribed and potent selective serotonin reuptake inhibitor frequently detected in surface waters. Fertilized FHM embryos were exposed to graded concentrations of FLX (confirmed at < LOD, 0.19, 0.74, 3.38, 10.2, 47.5 µg/L) for 32 days. Subsets of fish were subjected to omics and locomotor analyses at 7 days post-fertilization (dpf) and to histological and biometric measurements at 32 dpf. Enrichment analyses of transcriptomics and proteomics data revealed significant perturbations in gene sets associated with serotonergic and axonal functions. BMD analysis resulted in tPOD values of 0.56 µg/L (median of the 20 most sensitive gene-level BMDs), 5.0 µg/L (tenth percentile of all gene-level BMDs), 7.51 µg/L (mode of the first peak of all gene-level BMDs), and 5.66 µg/L (pathway-level BMD). These tPODs were protective of locomotor and reduced body weight effects (LOEC of 10.2 µg/L) observed in this study and were reflective of chronic apical BMDs of FLX reported in the literature. Furthermore, the distribution of gene-level BMDs followed a bimodal pattern, revealing disruption of sensitive neurotoxic pathways at low concentrations and metabolic pathway perturbations at higher concentrations. This is one of the first studies to derive protective tPODs for FLX using a short-term embryo assay at a life stage not considered to be a live animal under current legislations.


Asunto(s)
Cyprinidae , Contaminantes Químicos del Agua , Animales , Cyprinidae/genética , Fluoxetina/toxicidad , Larva , Transcriptoma
4.
J Surg Res ; 271: 137-144, 2021 Dec 09.
Artículo en Inglés | MEDLINE | ID: mdl-34896939

RESUMEN

BACKGROUND: The ACS-NSQIP surgical risk calculator (SRC) often guides preoperative counseling, but the rarity of complications in certain populations causes class imbalance, complicating risk prediction. We aimed to compare the performance of the ACS-NSQIP SRC to other classical machine learning algorithms trained on NSQIP data, and to demonstrate challenges and strategies in predicting such rare events. METHODS: Data from the NSQIP thyroidectomy module ys 2016 - 2018 were used to train logistic regression, Ridge regression and Random Forest classifiers for predicting 2 different composite outcomes of surgical risk (systemic and thyroidectomy-specific). We implemented techniques to address imbalanced class sizes and reported the area under the receiver operating characteristic (AUC) for each classifier including the ACS-NSQIP SRC, along with sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) at a 5% - 15% predicted risk threshold. RESULTS: Of 18,078 included patients, 405 (2.24%) patients suffered systemic complications and 1670 (9.24%) thyroidectomy-specific complications. Logistic regression performed best for predicting systemic complication risk (AUC 0.723 [0.658 - 0.778]); Random Forest with RUSBoost performed best for predicting thyroidectomy-specific complication risk (0.702; 0.674 - 0.726). The addition of optimizations for class imbalance improved performance for all classifiers. CONCLUSIONS: Complications are rare after thyroidectomy even when considered as composite outcomes, and class imbalance poses a challenge in surgical risk prediction. Using the SRC as a classifier where intervention occurs above a certain validated threshold, rather than citing the numeric estimates of complication risk, should be considered in low-risk patients.

5.
Genes (Basel) ; 12(12)2021 Nov 30.
Artículo en Inglés | MEDLINE | ID: mdl-34946888

RESUMEN

Saccharomyces cerevisiae has approximately 200 copies of the 35S rDNA gene, arranged tandemly on chromosome XII. This gene is transcribed by RNA polymerase I (Pol I) and the 35S rRNA transcript is processed to produce three of the four rRNAs required for ribosome biogenesis. An intergenic spacer (IGS) separates each copy of the 35S gene and contains the 5S rDNA gene, the origin of DNA replication, and the promoter for the adjacent 35S gene. Pol I is a 14-subunit enzyme responsible for the majority of rRNA synthesis, thereby sustaining normal cellular function and growth. The A12.2 subunit of Pol I plays a crucial role in cleavage, termination, and nucleotide addition during transcription. Deletion of this subunit causes alteration of nucleotide addition kinetics and read-through of transcription termination sites. To interrogate both of these phenomena, we performed native elongating transcript sequencing (NET-seq) with an rpa12Δ strain of S. cerevisiae and evaluated the resultant change in Pol I occupancy across the 35S gene and the IGS. Compared to wild-type (WT), we observed template sequence-specific changes in Pol I occupancy throughout the 35S gene. We also observed rpa12Δ Pol I occupancy downstream of both termination sites and throughout most of the IGS, including the 5S gene. Relative occupancy of rpa12Δ Pol I increased upstream of the promoter-proximal Reb1 binding site and dropped significantly downstream, implicating this site as a third terminator for Pol I transcription. Collectively, these high-resolution results indicate that the A12.2 subunit of Pol I plays an important role in transcription elongation and termination.

7.
J Biol Chem ; : 101450, 2021 Nov 25.
Artículo en Inglés | MEDLINE | ID: mdl-34838819

RESUMEN

Cancer cells are dependent upon an abundance of ribosomes to maintain rapid cell growth and proliferation. The rate-limiting step of ribosome biogenesis is ribosomal RNA (rRNA) synthesis by RNA polymerase I (Pol I). Therefore, a goal of the cancer therapeutic field is to develop and characterize Pol I inhibitors. Here, we elucidate the mechanism of Pol I inhibition by a first-in-class small molecule, BMH-21. To characterize the effects of BMH-21 on Pol I transcription, we leveraged high-resolution in vitro transcription assays and in vivo native elongating transcript sequencing (NET-seq). We find that Pol I transcription initiation, promoter-escape, and elongation are all inhibited by BMH-21 in vitro. In particular, the transcription elongation phase is highly sensitive to BMH-21 treatment, as it causes a decrease in transcription elongation rate and an increase in paused Pols on the ribosomal DNA (rDNA) template. In vivo NET-seq experiments complement these findings by revealing a reduction in Pol I occupancy on the template and an increase in sequence-specific pausing upstream of G-rich rDNA sequences after BMH-21 treatment. Collectively, these data reveal the mechanism of action of BMH-21, which is a critical step forward in the development of this compound and its derivatives for clinical use.

8.
Am Heart J ; 2021 Nov 01.
Artículo en Inglés | MEDLINE | ID: mdl-34736855

RESUMEN

Ticagrelor is often administered to patients with acute coronary syndromes. However, when these patients require urgent or emergent cardiothoracic (CT) surgery the presence of ticagrelor significantly increases surgical bleeding. The goal of the current trial is to evaluate the effectiveness and safety of the DrugSorb™-ATR hemoadsorption device for the intraoperative removal of ticagrelor to reduce postoperative bleeding in the above patient population. The Safe and Timely Antithrombotic Removal - Ticagrelor (STAR-T) Trial is a multi-center, double-blind, randomized, controlled trial enrolling patients who require cardiothoracic surgery on cardiopulmonary bypass (CPB) within 48 hours of last ticagrelor dose. Subjects will be randomized 1:1 to receive either the DrugSorb™-ATR device or an identical sham device during CPB. The study will enroll up to 120 subjects at 20 U.S centers, and the primary outcome is the composite of fatal perioperative bleeding, moderate/severe/massive bleeding according to the Universal Definition of Perioperative Bleeding in Cardiac Surgery (UDPB), and 24hr chest tube drainage. The components of the composite are hierarchically ranked according to clinical significance and the primary analysis will utilize the Win Ratio method. Percent change in ticagrelor levels before and after CPB (drug removal) will be the key secondary endpoint. An independent Clinical Events Committee will adjudicate all clinical endpoints including safety endpoints relating to postoperative thrombotic events. Subjects will be followed through 30 days after the index operation. The results from STAR-T, if positive, will potentially support FDA clearance of the device.

9.
Elife ; 102021 10 12.
Artículo en Inglés | MEDLINE | ID: mdl-34636723

RESUMEN

It remains challenging to understand why some hosts suffer severe illnesses, while others are unscathed by the same infection. We fitted a mathematical model to longitudinal measurements of parasite and red blood cell density in murine hosts from diverse genetic backgrounds to identify aspects of within-host interactions that explain variation in host resilience and survival during acute malaria infection. Among eight mouse strains that collectively span 90% of the common genetic diversity of laboratory mice, we found that high host mortality was associated with either weak parasite clearance, or a strong, yet imprecise response that inadvertently removes uninfected cells in excess. Subsequent cross-sectional cytokine assays revealed that the two distinct functional mechanisms of poor survival were underpinned by low expression of either pro- or anti-inflammatory cytokines, respectively. By combining mathematical modelling and molecular immunology assays, our study uncovered proximate mechanisms of diverse infection outcomes across multiple host strains and biological scales.


Asunto(s)
Eritrocitos/parasitología , Malaria/parasitología , Plasmodium chabaudi/patogenicidad , Animales , Simulación por Computador , Citocinas/sangre , Modelos Animales de Enfermedad , Susceptibilidad a Enfermedades , Interacciones Huésped-Parásitos , Mediadores de Inflamación/sangre , Malaria/sangre , Malaria/genética , Malaria/inmunología , Ratones de la Cepa 129 , Ratones Endogámicos C57BL , Ratones Endogámicos NOD , Modelos Inmunológicos , Carga de Parásitos , Plasmodium chabaudi/inmunología , Índice de Severidad de la Enfermedad , Especificidad de la Especie , Factores de Tiempo
10.
mBio ; 12(5): e0242421, 2021 Oct 26.
Artículo en Inglés | MEDLINE | ID: mdl-34607466

RESUMEN

Infections disrupt host metabolism, but the factors that dictate the nature and magnitude of metabolic change are incompletely characterized. To determine how host metabolism changes in relation to disease severity in murine malaria, we performed plasma metabolomics on eight Plasmodium chabaudi-infected mouse strains with diverse disease phenotypes. We identified plasma metabolic biomarkers for both the nature and severity of different malarial pathologies. A subset of metabolic changes, including plasma arginine depletion, match the plasma metabolomes of human malaria patients, suggesting new connections between pathology and metabolism in human malaria. In our malarial mice, liver damage, which releases hepatic arginase-1 (Arg1) into circulation, correlated with plasma arginine depletion. We confirmed that hepatic Arg1 was the primary source of increased plasma arginase activity in our model, which motivates further investigation of liver damage in human malaria patients. More broadly, our approach shows how leveraging phenotypic diversity can identify and validate relationships between metabolism and the pathophysiology of infectious disease. IMPORTANCE Malaria is a severe and sometimes fatal infectious disease endemic to tropical and subtropical regions. Effective vaccines against malaria-causing Plasmodium parasites remain elusive, and malaria treatments often fail to prevent severe disease. Small molecules that target host metabolism have recently emerged as candidates for therapeutics in malaria and other diseases. However, our limited understanding of how metabolites affect pathophysiology limits our ability to develop new metabolite therapies. By providing a rich data set of metabolite-pathology correlations and by validating one of those correlations, our work is an important step toward harnessing metabolism to mitigate disease. Specifically, we showed that liver damage in P. chabaudi-infected mice releases hepatic arginase-1 into circulation, where it may deplete plasma arginine, a candidate malaria therapeutic that mitigates vascular stress. Our data suggest that liver damage may confound efforts to increase levels of arginine in human malaria patients.

11.
Biophys Chem ; 279: 106682, 2021 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-34634538

RESUMEN

Parameter optimization or "data fitting" is a computational process that identifies a set of parameter values that best describe an experimental data set. Parameter optimization is commonly carried out using a computer program utilizing a non-linear least squares (NLLS) algorithm. These algorithms work by continuously refining a user supplied initial guess resulting in a systematic increase in the goodness of fit. A well-understood problem with this class of algorithms is that in the case of models with correlated parameters the optimized output parameters are initial guess dependent. This dependency can potentially introduce user bias into the resultant analysis. While many optimization programs exist, few address this dilemma. Here we present a data analysis tool, MENOTR, that is capable of overcoming the initial guess dependence in parameter optimization. Several case studies with published experimental data are presented to demonstrate the capabilities of this tool. The results presented here demonstrate how to effectively overcome the initial guess dependence of NLLS leading to greater confidence that the resultant optimized parameters are the best possible set of parameters to describe an experimental data set. While the optimization strategies implemented within MENOTR are not entirely novel, the application of these strategies to optimize parameters in kinetic and thermodynamic biochemical models is uncommon. MENOTR was designed to require minimal modification to accommodate a new model making it immediately accessible to researchers with a limited programming background. We anticipate that this toolbox can be used in a wide variety of data analysis applications. Prototype versions of this toolbox have been used in a number of published investigations already, as well as ongoing work with chemical-quenched flow, stopped-flow, and molecular tweezers data sets. STATEMENT OF SIGNIFICANCE: Non-linear least squares (NLLS) is a common form of parameter optimization in biochemistry kinetic and thermodynamic investigations These algorithms are used to fit experimental data sets and report corresponding parameter values. The algorithms are fast and able to provide good quality solutions for models involving few parameters. However, initial guess dependence is a well-known drawback of this optimization strategy that can introduce user bias. An alternative method of parameter optimization are genetic algorithms (GA). Genetic algorithms do not have an initial guess dependence but are slow at arriving at the best set of fit parameters. Here, we present MENOTR, a parameter optimization toolbox utilizing a hybrid GA/NLLS algorithm. The toolbox maximizes the strength of each strategy while minimizing the inherent drawbacks.

12.
Cardiol Ther ; 10(2): 561-568, 2021 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-34643895

RESUMEN

INTRODUCTION: This prospective pharmacodynamic (PD) study assessed the effect of the sodium-glucose co-transporter-2 inhibitor (SGLT2i), dapagliflozin, on platelet reactivity. METHODS: Patients with stable coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM) (n = 27) who were on maintenance dual antiplatelet therapy (DAPT) of aspirin 81 mg daily, and clopidogrel 75 mg daily were recruited. Platelet function was evaluated with the VerifyNow™ P2Y12 assay (Werfen, Bedford, MA, USA) and assessed prior to initiation of and after 10 days of treatment with dapagliflozin 10 mg once-daily dose regimen. Results were compared with a paired t test. RESULTS: Treatment with dapagliflozin significantly decreased P2Y12 reaction units (PRU) by 20%, (95% confidence interval (CI) 8.5-32.6%, p value 0.002). The mean difference in PRU was 36.70 (95% CI 16.66-56.75). No patients experienced any serious adverse events (SAEs). CONCLUSIONS: Significantly diminished platelet reactivity was observed on dapagliflozin as compared to without dapagliflozin. This dedicated pharmacodynamic study could be potentially informative and applicable for Trinidadian stable CAD patients with T2DM on DAPT. Further studies are required to confirm these exploratory findings. CLINICAL TRIAL REGISTRATION: EDGE ClinicalTrials.gov number NCT04400760.

13.
J Surg Res ; 270: 214-220, 2021 Oct 24.
Artículo en Inglés | MEDLINE | ID: mdl-34706298

RESUMEN

BACKGROUND: Up to 30% of thyroid nodules are classified as indeterminate after fine needle aspiration biopsy. These indeterminate thyroid nodules (ITNs) require surgical pathology for definitive diagnosis. Molecular testing provides additional pre-operative cancer risk stratification but adds expense and invasive testing. The purpose of this study is to utilize a machine learning (ML) algorithm to predict malignancy of ITNs using data available from less invasive tests. MATERIALS AND METHODS: We conducted a retrospective study using medical records from one academic and one community center. Thyroid nodules with an indeterminate diagnosis on fine needle aspiration biopsy and completed diagnostic pathology were included. Linear, non-linear, and non-linear-ensemble ML methods were tested for accuracy when predicting malignancy using 10-fold cross-validation. Classifiers were evaluated using area under the receiver operating characteristics curve (AUROC). RESULTS: A total of 355 nodules met inclusion criteria. Of these, 171 (48.2%) were diagnosed with cancer. A Random Forest classifier performed the best, producing an accuracy of 79.1%, a sensitivity of 75.5%, specificity of 82.4%, positive predicative value of 80.3%, negative predictive value of 79.0%, and an AUROC of 0.859. CONCLUSIONS: ML methods accurately risk stratify ITNs using data gathered from existing, non-invasive, and inexpensive diagnostic tests. Applying an ML model with existing data can become a cost-effective alternative to molecular testing. Future studies will prospectively evaluate the performance of this ML approach when combined with expert judgment.

14.
Nat Rev Immunol ; 21(10): 624-625, 2021 10.
Artículo en Inglés | MEDLINE | ID: mdl-34580465
15.
Biophys J ; 120(20): 4378-4390, 2021 10 19.
Artículo en Inglés | MEDLINE | ID: mdl-34509510

RESUMEN

RNA polymerases execute the first step in gene expression: transcription of DNA into RNA. Eukaryotes, unlike prokaryotes, express at least three specialized nuclear multisubunit RNA polymerases (Pol I, Pol II, and Pol III). RNA polymerase I (Pol I) synthesizes the most abundant RNA, ribosomal RNA. Nearly 60% of total transcription is devoted to ribosomal RNA synthesis, making it one of the cell's most energy consuming tasks. While a kinetic mechanism for nucleotide addition catalyzed by Pol I has been reported, it remains unclear to what degree different nucleotide sequences impact the incorporation rate constants. Furthermore, it is currently unknown if the previous investigation of a single-nucleotide incorporation was sensitive to the translocation step. Here, we show that Pol I exhibits considerable variability in both kmax and K1/2values using an in vitro multi-NTP incorporation assay measuring AMP and GMP incorporations. We found the first two observed nucleotide incorporations exhibited faster kmax-values (∼200 s-1) compared with the remaining seven positions (∼60 s-1). Additionally, the average K1/2 for ATP incorporation was found to be approximately threefold higher compared with GTP, suggesting Pol I has a tighter affinity for GTP compared with ATP. Our results demonstrate that Pol I exhibits significant variability in the observed rate constant describing each nucleotide incorporation. Understanding of the differences between the Pol enzymes will provide insight on the evolutionary pressures that led to their specialized roles. Therefore, the findings resulting from this work are critically important for comparisons with other polymerases across all domains of life.


Asunto(s)
Nucleótidos , ARN Polimerasa I , Catálisis , Cinética , ARN Polimerasa I/genética , ARN Polimerasa I/metabolismo , ARN Polimerasa II
16.
J Surg Res ; 268: 562-569, 2021 Aug 28.
Artículo en Inglés | MEDLINE | ID: mdl-34464894

RESUMEN

BACKGROUND: Thyroid nodules are common; up to 67% of adults will show nodules on high-quality ultrasound, and 95% of these nodules are benign. FNA cytology is a crucial step in determining the risk of malignancy, and a false negative diagnosis at this stage delays cancer treatment. The purpose of this study is to develop a predictive model using machine learning which can identify false negative FNA results based on less-invasive clinical data. MATERIALS AND METHODS: We conducted a retrospective medical record review at one academic and one community center. Inclusion criteria were thyroid nodules evaluated by ultrasound and FNA with a Bethesda II (benign) result or malignancy detected on pathology or FNA. Linear, non-linear, and ensemble models were generated with scikit-learn using 10-fold cross validation with repetition and compared with AUROC. The classification task was the prediction of malignancy using information acquired from less-invasive ultrasound and FNA. RESULTS: A total of 604 subjects met inclusion criteria; 38 were diagnosed with malignancy. Of all algorithms tested, a Random Forest method achieved the best AUROC (0.64) in separating benign and malignant nodules, though the improvement over other tested algorithms was not statistically significant. CONCLUSIONS: A Random Forest model performed better than random chance using readily available data obtained via standard evaluation of thyroid nodules. The diagnostic probability threshold of this model can be varied to minimize false positives at the cost of increasing the number of false negatives. Future studies will prospectively evaluate the model's performance.

17.
Environ Sci Technol ; 55(15): 10608-10618, 2021 08 03.
Artículo en Inglés | MEDLINE | ID: mdl-34292719

RESUMEN

There is an urgent demand for more efficient and ethical approaches in ecological risk assessment. Using 17α-ethinylestradiol (EE2) as a model compound, this study established an embryo benchmark dose (BMD) assay for rainbow trout (RBT; Oncorhynchus mykiss) to derive transcriptomic points-of-departure (tPODs) as an alternative to live-animal tests. Embryos were exposed to graded concentrations of EE2 (measured: 0, 1.13, 1.57, 6.22, 16.3, 55.1, and 169 ng/L) from hatch to 4 and up to 60 days post-hatch (dph) to assess molecular and apical responses, respectively. Whole proteome analyses of alevins did not show clear estrogenic effects. In contrast, transcriptomics revealed responses that were in agreement with apical effects, including excessive accumulation of intravascular and hepatic proteinaceous fluid and significant increases in mortality at 55.1 and 169 ng/L EE2 at later time points. Transcriptomic BMD analysis estimated the median of the 20th lowest geneBMD to be 0.18 ng/L, the most sensitive tPOD. Other estimates (0.78, 3.64, and 1.63 ng/L for the 10th percentile geneBMD, first peak geneBMD distribution, and median geneBMD of the most sensitive over-represented pathway, respectively) were within the same order of magnitude as empirically derived apical PODs for EE2 in the literature. This 4-day alternative RBT embryonic assay was effective in deriving tPODs that are protective of chronic effects of EE2.


Asunto(s)
Oncorhynchus mykiss , Contaminantes Químicos del Agua , Animales , Benchmarking , Estrógenos , Etinilestradiol/toxicidad , Oncorhynchus mykiss/genética , Transcriptoma , Contaminantes Químicos del Agua/toxicidad
18.
Clin Oral Implants Res ; 32(9): 1052-1060, 2021 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-34143522

RESUMEN

OBJECTIVES: To compare free-hand to computer-assisted implant planning and placement (CAIPP) regarding planned to achieved implant position. MATERIAL AND METHODS: Forty-eight cast/bone models were mounted in mannequin heads. On each side, a tooth gap of different sizes was created. In the test group (T), study implants were placed using a CAD-CAM guide based on virtual planning. In the control (C), free-hand implant placement was performed. After CBCT scanning, the implant position was compared with the planned position. Descriptive statistics were applied, and ANOVA was used to identify differences between groups and gaps. (p < .05). RESULTS: In C, mean lateral deviations at the implant base amounted to 0.7 mm (max. 1.8) (large gap) and 0.49 mm (1.22) (small gap). In T, 0.18 mm (0.49) and 0.24 mm (0.52) were recorded. At the apex, 0.77 mm (2.04) (large gap) and 0.51 mm (1.24) (small gap) were measured in C, and 0.31 mm (0.83)/0.34 mm (0.93) in T. Mean vertical deviations in C measured 0.46 mm (1.26) (large gap) and 0.45 mm (1.7) (small gap). In T, 0.14 mm (0.44) and 0.28 mm (0.78) were recorded. Mean angular deviations of 1.7° (3.2°) were observed in C (large gap) and 1.36° (2.1°) (small gap). In T, mean values were 1.57° (3.3°) and 1.32° (3.4°). Lateral and vertical deviations were significantly different between groups (not gaps), angular between gaps (not groups). CONCLUSIONS: CAIPP protocols showed smaller deviations irrespective of the size of the tooth gap. In C, the gap size had an influence on the error in angulation only.


Asunto(s)
Implantes Dentales , Cirugía Asistida por Computador , Diseño Asistido por Computadora , Computadores , Tomografía Computarizada de Haz Cónico , Implantación Dental Endoósea , Imagenología Tridimensional , Planificación de Atención al Paciente
19.
Genet Sel Evol ; 53(1): 52, 2021 Jun 19.
Artículo en Inglés | MEDLINE | ID: mdl-34147084

RESUMEN

Expression of the cellular prion protein (PrPC) is crucial for the development of prion diseases. Amino acid changes in PrPC or a reduced amount of PrPC may modulate disease resistance. The relative abundance of C1, a natural α-cleavage fragment of PrPC, was previously found to be associated with a resistant PRNP genotype in sheep. Goats are another small ruminant where classical scrapie susceptibility is under strong genetic control. In this study, we assessed PrPC in goats for the existence of similar associations between PrPC fragments and genotype. Brain tissue homogenates from scrapie-free goats with wild type PRNP or polymorphisms (I142M, H143R, N146S, or Q222K) were deglycosylated prior to immunoblot for assessment of the relative abundance of the C1 fragment of PrPC. The presence of K222 or S146 alleles demonstrated significantly different relative levels of C1 compared to that observed in wild type goats, which suggests that the genotype association with C1 is neither unique to sheep nor exclusive to the ovine Q171R dimorphism.


Asunto(s)
Cabras/genética , Polimorfismo de Nucleótido Simple , Proteínas Priónicas/genética , Proteolisis , Animales , Encéfalo/metabolismo , Mutación Missense , Proteínas Priónicas/metabolismo
20.
Appl Clin Inform ; 12(3): 445-458, 2021 05.
Artículo en Inglés | MEDLINE | ID: mdl-34107542

RESUMEN

BACKGROUND: The COVID-19 pandemic led to dramatic increases in telemedicine use to provide outpatient care without in-person contact risks. Telemedicine increases options for health care access, but a "digital divide" of disparate access may prevent certain populations from realizing the benefits of telemedicine. OBJECTIVES: The study aimed to understand telemedicine utilization patterns after a widespread deployment to identify potential disparities exacerbated by expanded telemedicine usage. METHODS: We performed a cross-sectional retrospective analysis of adults who scheduled outpatient visits between June 1, 2020 and August 31, 2020 at a single-integrated academic health system encompassing a broad range of subspecialties and a large geographic region in the Upper Midwest, during a period of time after the initial surge of COVID-19 when most standard clinical services had resumed. At the beginning of this study period, approximately 72% of provider visits were telemedicine visits. The primary study outcome was whether a patient had one or more video-based visits, compared with audio-only (telephone) visits or in-person visits only. The secondary outcome was whether a patient had any telemedicine visits (video-based or audio-only), compared with in-person visits only. RESULTS: A total of 197,076 individuals were eligible (average age = 46 years, 56% females). Increasing age, rural status, Asian or Black/African American race, Hispanic ethnicity, and self-pay/uninsured status were significantly negatively associated with having a video visit. Digital literacy, measured by patient portal activation status, was significantly positively associated with having a video visit, as were Medicaid or Medicare as payer and American Indian/Alaskan Native race. CONCLUSION: Our findings reinforce previous evidence that older age, rural status, lower socioeconomic status, Asian race, Black/African American race, and Hispanic/Latino ethnicity are associated with lower rates of video-based telemedicine use. Health systems and policies should seek to mitigate such barriers to telemedicine when possible, with efforts such as digital literacy outreach and equitable distribution of telemedicine infrastructure.


Asunto(s)
COVID-19/epidemiología , Accesibilidad a los Servicios de Salud/estadística & datos numéricos , Disparidades en Atención de Salud/estadística & datos numéricos , Pandemias/estadística & datos numéricos , Telemedicina/estadística & datos numéricos , Adolescente , Adulto , Anciano , Estudios Transversales , Femenino , Humanos , Masculino , Persona de Mediana Edad , Estudios Retrospectivos , Adulto Joven
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