Search

Abstract We developed a mathematical model for autologous stem cell therapy to cure sickle cell disease (SCD). Experimental therapies using this approach seek to engraft stem cells containing a curative gene. These stem cells are expected to produce a lifelong supply of red blood cells (RBCs) containing an anti‐sickling hemoglobin. This complex, multistep treatment is expensive, and there is limited patient data available from early clinical trials. Our objective was to quantify the impact of treatment parameters, such as initial stem cell dose, efficiency of lentiviral transduction, and degree of bone marrow preconditioning on engraftment efficiency, peripheral RBC numbers, and anti‐sickling hemoglobin levels over time. We used ordinary differential equations to model RBC production from progenitor cells in the bone marrow, and hemoglobin assembly from its constituent globin monomers. The model recapitulates observed RBC and hemoglobin levels in healthy and SCD phenotypes. Treatment simulations predict dynamics of stem cell engraftment and RBC containing the therapeutic gene product. Post‐treatment dynamics show an early phase of reconstitution due to short lived stem cells, followed by a sustained RBC production from stable engraftment of long‐term stem cells. This biphasic behavior was previously reported in the literature. Sensitivity analysis of the model quantified relationships between treatment parameters and efficacy. The initial dose of transduced stem cells, and the intensity of myeloablative bone marrow preconditioning are predicted to most positively impact long‐term outcomes. The quantitative systems pharmacology approach used here demonstrates the value of model‐assisted therapeutic design for gene therapies in SCD.

ObjectivesCardiovascular disease (CVD) risk calculators developed for the general population do not accurately predict CVD events in patients with RA. We sought to externally validate risk calculators recommended for use in patients with RA including the EULAR 1.5 multiplier, the Expanded Cardiovascular Risk Prediction Score for RA (ERS-RA) and QRISK2.MethodsSeven RA cohorts from UK, Norway, Netherlands, USA, South Africa, Canada and Mexico were combined. Data on baseline CVD risk factors, RA characteristics and CVD outcomes (including myocardial infarction, ischaemic stroke and cardiovascular death) were collected using standardized definitions. Performance of QRISK2, EULAR multiplier and ERS-RA was compared with other risk calculators [American College of Cardiology/American Heart Association (ACC/AHA), Framingham Adult Treatment Panel III Framingham risk score-Adult Treatment Panel (FRS-ATP) and Reynolds Risk Score] using c-statistics and net reclassification index.ResultsAmong 1796 RA patients without prior CVD [mean ( s . d .) age: 54.0 (14.0) years, 74% female], 100 developed CVD events during a mean follow-up of 6.9 years (12430 person-years). Estimated CVD risk by ERS-RA [mean ( s . d .) 8.8% (9.8%)] was comparable to FRS-ATP [mean ( s . d .) 9.1% (8.3%)] and Reynolds [mean ( s . d .) 9.2% (12.2%)], but lower than ACC/AHA [mean ( s . d .) 9.8% (12.1%)]. QRISK2 substantially overestimated risk [mean ( s . d .) 15.5% (13.9%)]. Discrimination was not improved for ERS-RA (c-statistic = 0.69), QRISK2 or EULAR multiplier applied to ACC/AHA compared with ACC/AHA (c-statistic = 0.72 for all) or for FRS-ATP (c-statistic = 0.75). The net reclassification index for ERS-RA was low (-0.8% vs ACC/AHA and 2.3% vs FRS-ATP).ConclusionThe QRISK2, EULAR multiplier and ERS-RA algorithms did not predict CVD risk more accurately in patients with RA than CVD risk calculators developed for the general population.

BackgroundAs more health care organizations transition to using electronic health record (EHR) systems, it is important for these organizations to maximize the secondary use of their data to support service improvement and clinical research. These organizations will find it challenging to have systems capable of harnessing the unstructured data fields in the record (clinical notes, letters, etc) and more practically have such systems interact with all of the hospital data systems (legacy and current). ObjectiveWe describe the deployment of the EHR interfacing information extraction and retrieval platform CogStack at University College London Hospitals (UCLH). MethodsAt UCLH, we have deployed the CogStack platform, an information retrieval platform with natural language processing capabilities. The platform addresses the problem of data ingestion and harmonization from multiple data sources using the Apache NiFi module for managing complex data flows. The platform also facilitates the extraction of structured data from free-text records through use of the MedCAT natural language processing library. Finally, data science tools are made available to support data scientists and the development of downstream applications dependent upon data ingested and analyzed by CogStack. ResultsThe platform has been deployed at the hospital, and in particular, it has facilitated a number of research and service evaluation projects. To date, we have processed over 30 million records, and the insights produced from CogStack have informed a number of clinical research use cases at the hospital. ConclusionsThe CogStack platform can be configured to handle the data ingestion and harmonization challenges faced by a hospital. More importantly, the platform enables the hospital to unlock important clinical information from the unstructured portion of the record using natural language processing technology.

Background Sarcoidosis is an inflammatory, noncaseating, granulomatous disorder of unknown cause that can affect any body system and is associated with cardiovascular disease including sudden cardiac death (SCD). Cardiac involvement in sarcoidosis is associated with higher risk of SCD, but the SCD risk in the general sarcoidosis population is unknown. We aimed to determine the risk of SCD in people with sarcoidosis versus the matched general population. Methods and Results A population‐based cohort of sarcoidosis and age‐ and sex‐matched comparators from January 1, 1976 to December 31, 2013 was used; presence of other comorbidities in the comparator group was not an exclusion criterion. Mortality, including time, place, and cause of death were measured and manually adjudicated for SCD events. Incidence rates are reported per 100 000 person‐years, and Cox models were used for group comparisons. Of the 345 incident cases of sarcoidosis (171 men; 50%) there were 58 reported deaths; 10 were definite/probable SCD versus 57 all‐cause and 9 SCDs in comparators. Median follow‐up was 12.9 years (interquartile range, 6.0–23.4 years) . Incidence rate of SCD in sarcoidosis was 192 (95% CI, 92–352) versus 155 (95% CI, 71–294) in comparators (hazard ratio [HR], 1.28 (95% CI, 0.52–3.17). Nocturnal deaths were more frequent in sarcoidosis 57 (95% CI, 12–168) versus 17 (95% CI, 0.4–95) (HR, 3.76 [95% CI, 0.39–36.47]). No significant differences were detected between the groups by sex, age, calendar year of diagnosis, or disease duration. Conclusions In a population‐based cohort of patients with sarcoidosis, the risk for SCD compared with matched comparators was not increased. There were more nocturnal deaths among patients with sarcoidosis, yet this was statistically insignificant.

The application of model-informed drug discovery and development (MID3) approaches in the early stages of drug discovery can help determine feasibility of drugging a target, prioritize between targets, or define optimal drug properties for a target product profile (TPP). However, applying MID3 in early discovery can be challenging due to the lack of pharmacokinetic (PK) and pharmacodynamic (PD) data at this stage. Early Feasibility Assessment (EFA) is the application of mechanistic PKPD models, built from first principles, and parameterized by data that is readily available early in drug discovery to make effective dose predictions. This manuscript demonstrates the ability of EFA to make accurate predictions of clinical effective doses for nine approved biotherapeutics and outlines the potential of extending this approach to novel therapeutics to impact early drug discovery decisions.

This paper presents experimental testing evaluating the ability of a bridge deck deicing system to mitigate concrete deterioration from thermal stresses, frost action, and early-age cracking. Two experimental bridge deck models were constructed with embedded heat exchanger tubing and instrumented with thermocouples and strain gauges. Model 1 evaluated the efficiency of a deicing system in deicing and mitigating concrete deterioration from thermal stresses and frost action in concrete bridge decks, while Model 2 tested the effect of a deicing system on early-age cracking in bridge decks. The models were tested in a cold chamber laboratory under conditions representative of Montana's winter weather, with the system circulating warm fluid through the decks. Results showed the system succeeded in increasing concrete temperatures at all depths. While the system did not always raise temperatures above freezing, the consistent increases suggested that the system could enable deicing and mitigate frost action given certain conditions and higher inlet fluid temperatures. The system also successfully decreased thermal movement strain by up to 40% and reduced thermal shrinkage by decreasing the difference between peak cured and stabilized temperatures. Although the system did not eliminate thermal gradients, the maximum gradient induced was insignificant. Further testing is needed on strength impacts. Overall, the deicing system showed promise to reduce thermally induced deterioration in concrete bridge decks by regulating temperatures. [ABSTRACT FROM AUTHOR]

Background. Often, conflicts occur in modern business. However, business disputes can be very detrimental to a company financially and to its reputation. Therefore, the role of corporate law firms in preventing and handling business disputes is becoming increasingly important. A corporate law firm can help manage risk and minimize the possibility of disputes. Purpose: The purpose of this research is to study how corporate law firms prevent business disputes. The focus of the research is to understand how they spot potential disputes, create strategies to prevent them, and how they handle disputes that arise. The main aim of this research is to provide deeper insight into how effective the role of corporate law firms is in reducing the risk of business disputes. Method. This research was conducted using a structured interview method. Members of corporate law firms who have relevant knowledge and experience in managing business disputes are the respondents interviewed. Using pre-prepared interview guidelines, interviews are conducted in person or via a virtual platform. Next, qualitative analysis was carried out on the interview data to find patterns, themes and important findings. Results. The research results show that corporate law firms are very important in preventing business disputes. To avoid disputes, respondents create clear contracts, provide training to employees, and monitor changes in legislation. Company authorities also handle disputes using mediation, negotiation, and arbitration. Conclusion. The study found that corporate law firms play a very important role in preventing and handling business disputes. By using the right strategy and proactively involving various parties, corporate law firms can help companies reduce risks and reduce the negative impact of business disputes. Therefore, investment in the development of a corporate law firm can be considered as feasible. [ABSTRACT FROM AUTHOR]

Social media platforms have been adapted into society in various ways during last two decades. Few studies have examined social media content from the perspective of the individual library professional, and in particular, from librarians' social media posts about their work. This research explores social media complaints from library professionals to reveal insights into the areas of concern related to libraries as expressed in an informal, discursive style. Reddit data from three library subReddits was collected through a Python script. A total of 272 complaint posts with enough information were coded manually. A computational tool, Linguistic Inquiry and Word Count (LIWC), was also used to extract linguistic characteristics of each post. The majority of the sources of the complaint posts came from librarians (86.76%). The top five categories of the target of the complaints were patrons (27.94%), the poster's organization (20.22%), the poster's supervisor (11.03%), the library field (11.03%), and the poster's coworkers (10.29%). The top four topics of the complaint posts were patron behavior (21.69%), negative work environment (16.18%), job expectations (11.76%), and service expectations (10.66%). Organizations should put into place mechanisms and processes through which employees may share their concerns and exercise their voice, with no retribution, to solve workplace problems. [ABSTRACT FROM AUTHOR]

This article proposes novel methods to test for simultaneous diagonalization of possibly asymmetric matrices. Motivated by various applications, a two-sample test as well as a generalization for multiple matrices are proposed. A partial version of the test is also studied to check whether a partial set of eigenvectors is shared across samples. Additionally, a novel algorithm for the considered testing methods is introduced. Simulation studies demonstrate favorable performance for all designs. Finally, the theoretical results are used to decouple multiple vector autoregression models into univariate time series, and to test for the same stationary distribution in recurrent Markov chains. These applications are demonstrated using macroeconomic indices of eight countries and streamflow data, respectively. for this article are available online. [ABSTRACT FROM AUTHOR]

Abstract Background In the United states obesity and socioeconomic status (SES), or one’s standing in society based on income, education, and/or occupation, are strongly associated. The mechanisms for this relationship may include having high levels of motivation to get food (reinforcing value of food; RRV) and low levels of inhibitory control (delay discounting; DD) which, when combined, is referred to as reinforcement pathology (RP). We sought to examine the relationships among multiple measures of household SES, RP, and age-adjusted body mass index (zBMI) among adolescents. Methods These data were collected as part of ongoing longitudinal study of risk factors for obesity in 244 adolescents. The adolescents and one parent/guardian had height and weight measured and completed surveys. The adolescents completed an adjusting amount DD task and a computer-based RRV task. Analyses consisted of correlations among measures of SES and RRV, DD, and BMI z-scores. In the case of significant associations, multiple regression models were created with theoretically informed covariates. Results Household income, parent/guardian education, parent/guardian occupation, and food insecurity status were all related to one another. Among the adolescents, a significant portion of the variance in RRV was accounted for by household income after controlling for covariates. For DD, it was parent/guardian education that was most associated after controlling for covariates. Conclusion When low income and low parent/guardian education occur together, there may be an increased risk of RP. Separately, food insecurity was predictive of higher parent/guardian BMI. Future research should continue to explore the effects of low income and parent/guardian education on RP among youth by examining them over time.