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Nevin Manimala Statistics

Acceleration of Solvation Free Energy Calculation via Thermodynamic Integration Coupled with Gaussian Process Regression and Improved Gelman-Rubin Convergence Diagnostics

J Chem Theory Comput. 2024 Mar 12. doi: 10.1021/acs.jctc.3c01381. Online ahead of print.

ABSTRACT

The determination of the solvation free energy of ions and molecules holds profound importance across a spectrum of applications spanning chemistry, biology, energy storage, and the environment. Molecular dynamics simulations are powerful tools for computing this critical parameter. Nevertheless, the accurate and efficient calculation of the solvation free energy becomes a formidable endeavor when dealing with complex systems characterized by potent Coulombic interactions and sluggish ion dynamics and, consequently, slow transition across various metastable states. In the present study, we expose limitations stemming from the conventional calculation of the statistical inefficiency g in the thermodynamic integration method, a factor that can hinder the determination of convergence of the solvation free energy and its associated uncertainty. Instead, we propose a robust scheme based on Gelman-Rubin convergence diagnostics. We leverage this improved estimation of uncertainties to introduce an innovative accelerated thermodynamic integration method based on the Gaussian Process regression. This methodology is applied to the calculation of the solvation free energy of trivalent rare-earth elements immersed in ionic liquids, a scenario in which the aforementioned challenges render standard approaches ineffective. The proposed method proves to be effective in computing solvation free energy in situations where traditional thermodynamic integration methods fall short.

PMID:38470415 | DOI:10.1021/acs.jctc.3c01381

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Nevin Manimala Statistics

Outcome of patients with relapsed or refractory nonrhabdomyosarcoma soft tissue sarcomas enrolled in phase 2 cooperative group clinical trials: A report from the Children’s Oncology Group

Cancer. 2024 Mar 12. doi: 10.1002/cncr.35276. Online ahead of print.

ABSTRACT

BACKGROUND: The aim of this study was to estimate the event-free survival (EFS) of children and young adults with relapsed or refractory nonrhabdomyosarcoma soft tissue sarcoma (NRSTS) treated in nonrandomized phase 2 studies conducted by the Children’s Oncology Group (COG) and predecessor groups to establish a benchmark EFS for future phase 2 NRSTS trials evaluating the activity of novel agents.

METHODS: A retrospective analysis of patients with recurrent or refractory NRSTS prospectively enrolled in nonrandomized phase 2 COG and predecessor group trials between 1994 and 2015 was conducted. EFS was defined as disease progression/relapse or death and calculated via the Kaplan-Meier method. The log-rank test and relative risk regression were used to compare EFS distribution by age at enrollment, sex, race, NRSTS histology, prior lines of therapy, calendar year of trial, and type of radiographic response.

RESULTS: In total, 137 patients were enrolled in 13 phase 2 trials. All trials used radiographic response rate as a primary outcome, and none of the agents used were considered active on the basis of trial-specified thresholds. The estimated median EFS and 6-month EFS of the entire study cohort was 1.5 months (95% confidence interval [CI], 1.3-1.8 months) and 19.4% (95% CI, 12.7%-26%), respectively. No difference in EFS was observed by age at enrollment, sex, race, NRSTS histology subtype, prior lines of therapies, and trial initiation year. EFS significantly differed by radiographic response.

CONCLUSIONS: The EFS for children and young adults with relapsed or refractory NRSTS remains suboptimal. Established EFS can be referenced as a benchmark for future single-agent phase 2 trials incorporating potentially active novel agents in this population.

PMID:38470405 | DOI:10.1002/cncr.35276

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Nevin Manimala Statistics

Accidental Hypothermia in the Largest Emergency Hospital in North-Eastern Romania

Rom J Intern Med. 2024 Mar 12. doi: 10.2478/rjim-2024-0010. Online ahead of print.

ABSTRACT

INTRODUCTION: Accidental hypothermia (AH) presents a significant mortality risk, even in individuals with good health. Early recognition of the parameters associated with negative prognosis could save more lives.

METHODS: This was a pilot, retrospective observational study, conducted in the largest Emergency Hospital in North Eastern Romania, which included all patients with AH (defined as body temperature below 35°C), hospitalized and treated in our hospital between 2019 and 2022.

RESULTS: A total of 104 patients with AH were included in our study, 90 of whom had data collected and statistically analyzed. The clinical, biological, and therapeutic parameters associated with negative outcomes were represented by a reduced GCS score (p=0.024), diminished systolic and diastolic blood pressure (p=0.007 respectively, 0.013), decreased bicarbonate (p=0.043) and hemoglobin levels (p=0.002), the presence of coagulation disorders (p=0.007), as well as the need for administration of inotropic or vasopressor medications (p=0.04).

CONCLUSION: In this pilot, retrospective, observational study, the negative outcomes observed in patients with AH hospitalized in the largest Emergency Hospital in North-Eastern Romania were associated with several clinical, biochemical, and therapeutic factors, which are easy to identify in clinical practice. Recognizing the significance of these associated factors empowers healthcare practitioners to intervene at an early stage to save more lives.

PMID:38470364 | DOI:10.2478/rjim-2024-0010

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Nevin Manimala Statistics

Size Isn’t Everything: Geometric Tuning in Polycyclic Aromatic Hydrocarbons and Its Implications for Carbon Nanodots

J Phys Chem A. 2024 Mar 12. doi: 10.1021/acs.jpca.3c07416. Online ahead of print.

ABSTRACT

Recent developments in light-emitting carbon nanodots and molecular organic semiconductors have seen renewed interest in the properties of polycyclic aromatic hydrocarbons (PAHs) as a family. The networks of delocalized π electrons in sp2-hybridized carbon grant PAHs light-emissive properties right across the visible spectrum. However, the mechanistic understanding of their emission energy has been limited due to the ground state-focused methods of determination. This computational chemistry work, therefore, seeks to validate existing rules and elucidate new features and characteristics of PAHs that influence their emissions. Predictions based on (time-dependent) density functional theory account for the full 3-dimensional electronic structure of ground and excited states and reveal that twisting and near-degeneracies strongly influence emission spectra and may therefore be used to tune the color of PAHs and, hence, carbon nanodots. We particularly note that the influence of twisting goes beyond torsional destabilization of the ground-state and geometric relaxation of the excited state, with a third contribution associated with the electric transition dipole. Symmetries and peri-condensation may also have an effect, but this could not be statistically confirmed. In pursuing this goal, we demonstrate that with minimal changes to molecular size, the entire visible spectrum may be spanned by geometric modification alone; we have also provided a first estimate of emission energy for 35 molecules currently lacking published emission spectra as well as clear guidelines for when more sophisticated computational techniques are required to predict the properties of PAHs accurately.

PMID:38470339 | DOI:10.1021/acs.jpca.3c07416

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Nevin Manimala Statistics

The Daily Fact Pile: Exploring Mutual Microlearning in Neurology Resident Education

Teach Learn Med. 2024 Mar 12:1-12. doi: 10.1080/10401334.2024.2326477. Online ahead of print.

ABSTRACT

Problem: A significant proportion of learning during residency takes place through informal channels. Spontaneous collaboration among medical learners significantly contributes to this informal learning and is increasingly recognized as a component of the hidden curriculum in medical education. Yet historically, a disproportionate emphasis in medical education has been placed on didactic, structured, and faculty-initiated methods, leaving an important force in medical education understudied and underutilized. We hypothesize that there is significant educational potential in studying and deploying targeted tools to facilitate collaboration among medical learners. Intervention: At our institution, neurology residents implemented the “Daily Fact Pile” (DFP), a resident-led, email-based collaboration that served as a platform to share clinical pearls in an informal, digital way. Participation was voluntary and participants were encouraged to share facts that were new to them and thought to be clinically relevant. Motivated by the positive collective experience, we conducted a retrospective examination of this phenomenon. In this context, we developed the concept of “mutual microlearning” to characterize this efficient, multidirectional exchange of information. Context: Thirty-six residents in a single neurology residency program utilized the DFP at a large university hospital in the USA between 2018 and 2019. After 21 months of spontaneous and voluntary participation, we assessed the feasibility of the DFP, its impact on the education and morale of neurology residents, and compared its mutual microlearning approach to traditional lectures. This was done through a survey of the DFP participants with a response rate of 80.7%, and analysis of the statistics of participation and interaction with the DFP. Impact: Most participants felt that the DFP was beneficial to their education and thought they often or always learned something new from reading the DFP. The impact of the DFP extended beyond education by improving interest in neurology, morale, and sense of teamwork. The DFP was feasible during neurology residency and participation was high, though participants were more likely to read facts than share them. Lessons learned: Mutual microlearning represents an opportunity to augment residents’ education, and well-designed mutual microlearning tools hold promise for complementing traditional teaching methods. We learned that efficiency, ease of use, and a supportive, non-judgmental environment are all essential to the success of such tools. Future research should delve deeper into the underlying mechanisms of mutual microlearning to establish its position within the theoretical frameworks of medical education.

PMID:38470305 | DOI:10.1080/10401334.2024.2326477

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Nevin Manimala Statistics

Inferring a directed acyclic graph of phenotypes from GWAS summary statistics

Biometrics. 2024 Jan 29;80(1):ujad039. doi: 10.1093/biomtc/ujad039.

ABSTRACT

Estimating phenotype networks is a growing field in computational biology. It deepens the understanding of disease etiology and is useful in many applications. In this study, we present a method that constructs a phenotype network by assuming a Gaussian linear structure model embedding a directed acyclic graph (DAG). We utilize genetic variants as instrumental variables and show how our method only requires access to summary statistics from a genome-wide association study (GWAS) and a reference panel of genotype data. Besides estimation, a distinct feature of the method is its summary statistics-based likelihood ratio test on directed edges. We applied our method to estimate a causal network of 29 cardiovascular-related proteins and linked the estimated network to Alzheimer’s disease (AD). A simulation study was conducted to demonstrate the effectiveness of this method. An R package sumdag implementing the proposed method, all relevant code, and a Shiny application are available.

PMID:38470257 | DOI:10.1093/biomtc/ujad039

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Nevin Manimala Statistics

Diagnostics for regression models with semicontinuous outcomes

Biometrics. 2024 Jan 29;80(1):ujae007. doi: 10.1093/biomtc/ujae007.

ABSTRACT

Semicontinuous outcomes commonly arise in a wide variety of fields, such as insurance claims, healthcare expenditures, rainfall amounts, and alcohol consumption. Regression models, including Tobit, Tweedie, and two-part models, are widely employed to understand the relationship between semicontinuous outcomes and covariates. Given the potential detrimental consequences of model misspecification, after fitting a regression model, it is of prime importance to check the adequacy of the model. However, due to the point mass at zero, standard diagnostic tools for regression models (eg, deviance and Pearson residuals) are not informative for semicontinuous data. To bridge this gap, we propose a new type of residuals for semicontinuous outcomes that is applicable to general regression models. Under the correctly specified model, the proposed residuals converge to being uniformly distributed, and when the model is misspecified, they significantly depart from this pattern. In addition to in-sample validation, the proposed methodology can also be employed to evaluate predictive distributions. We demonstrate the effectiveness of the proposed tool using health expenditure data from the US Medical Expenditure Panel Survey.

PMID:38470256 | DOI:10.1093/biomtc/ujae007

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Nevin Manimala Statistics

A method to correct for local alterations in DNA copy number that bias functional genomics assays applied to antibiotic-treated bacteria

mSystems. 2024 Mar 12:e0066523. doi: 10.1128/msystems.00665-23. Online ahead of print.

ABSTRACT

Functional genomics techniques, such as transposon insertion sequencing and RNA-sequencing, are key to studying relative differences in bacterial mutant fitness or gene expression under selective conditions. However, certain stress conditions, mutations, or antibiotics can directly interfere with DNA synthesis, resulting in systematic changes in local DNA copy numbers along the chromosome. This can lead to artifacts in sequencing-based functional genomics data when comparing antibiotic treatment to an unstressed control. Further, relative differences in gene-wise read counts may result from alterations in chromosomal replication dynamics, rather than selection or direct gene regulation. We term this artifact “chromosomal location bias” and implement a principled statistical approach to correct it by calculating local normalization factors along the chromosome. These normalization factors are then directly incorporated into statistical analyses using standard RNA-sequencing analysis methods without modifying the read counts themselves, preserving important information about the mean-variance relationship in the data. We illustrate the utility of this approach by generating and analyzing a ciprofloxacin-treated transposon insertion sequencing data set in Escherichia coli as a case study. We show that ciprofloxacin treatment generates chromosomal location bias in the resulting data, and we further demonstrate that failing to correct for this bias leads to false predictions of mutant drug sensitivity as measured by minimum inhibitory concentrations. We have developed an R package and user-friendly graphical Shiny application, ChromoCorrect, that detects and corrects for chromosomal bias in read count data, enabling the application of functional genomics technologies to the study of antibiotic stress.IMPORTANCEAltered gene dosage due to changes in DNA replication has been observed under a variety of stresses with a variety of experimental techniques. However, the implications of changes in gene dosage for sequencing-based functional genomics assays are rarely considered. We present a statistically principled approach to correcting for the effect of changes in gene dosage, enabling testing for differences in the fitness effects or regulation of individual genes in the presence of confounding differences in DNA copy number. We show that failing to correct for these effects can lead to incorrect predictions of resistance phenotype when applying functional genomics assays to investigate antibiotic stress, and we provide a user-friendly application to detect and correct for changes in DNA copy number.

PMID:38470252 | DOI:10.1128/msystems.00665-23

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Nevin Manimala Statistics

Assessment of Right Atrial Function Measured with Cardiac MRI Feature Tracking for Predicting Outcomes in Patients with Dilated Cardiomyopathy

Radiology. 2024 Mar;310(3):e232388. doi: 10.1148/radiol.232388.

ABSTRACT

Background Right atrial (RA) function strain is increasingly acknowledged as an important predictor of adverse events in patients with diverse cardiovascular conditions. However, the prognostic value of RA strain in patients with dilated cardiomyopathy (DCM) remains uncertain. Purpose To evaluate the prognostic value of RA strain derived from cardiac MRI (CMR) feature tracking (FT) in patients with DCM. Materials and Methods This multicenter, retrospective study included consecutive adult patients with DCM who underwent CMR between June 2010 and May 2022. RA strain parameters were obtained using CMR FT. The primary end points were sudden or cardiac death or heart transplant. Cox regression analysis was used to determine the association of variables with outcomes. Incremental prognostic value was evaluated using C indexes and likelihood ratio tests. Results A total of 526 patients with DCM (mean age, 51 years ± 15 [SD]; 381 male) were included. During a median follow-up of 41 months, 79 patients with DCM reached the primary end points. At univariable analysis, RA conduit strain was associated with the primary end points (hazard ratio [HR], 0.82 [95% CI: 0.76, 0.87]; P < .001). In multivariable Cox analysis, RA conduit strain was an independent predictor for the primary end points (HR, 0.83 [95% CI: 0.77, 0.90]; P < .001). A model combining RA conduit strain with other clinical and conventional imaging risk factors (C statistic, 0.80; likelihood ratio, 92.54) showed improved discrimination and calibration for the primary end points compared with models with clinical variables (C statistic, 0.71; likelihood ratio, 37.12; both P < .001) or clinical and imaging variables (C statistic, 0.75; likelihood ratio, 64.69; both P < .001). Conclusion CMR FT-derived RA conduit strain was an independent predictor of adverse outcomes among patients with DCM, providing incremental prognostic value when combined in a model with clinical and conventional CMR risk factors. Published under a CC BY 4.0 license. Supplemental material is available for this article.

PMID:38470238 | DOI:10.1148/radiol.232388

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Nevin Manimala Statistics

Shared and Distinct Genomics of Chronic Thromboembolic Pulmonary Hypertension and Pulmonary Embolism

Am J Respir Crit Care Med. 2024 Mar 12. doi: 10.1164/rccm.202307-1236OC. Online ahead of print.

ABSTRACT

RATIONALE: Chronic Thromboembolic Pulmonary Hypertension involves formation and non-resolution of thrombus, dysregulated inflammation, angiogenesis and the development of a small vessel vasculopathy.

OBJECTIVES: We aimed to establish the genetic basis of chronic thromboembolic pulmonary hypertension to gain insight into its pathophysiological contributors.

METHODS: We conducted a genome-wide association study on 1907 European cases and 10363 European controls. We co-analysed our results with existing results from genome-wide association studies on deep vein thrombosis, pulmonary embolism and idiopathic pulmonary arterial hypertension.

MEASUREMENTS AND MAIN RESULTS: Our primary association study revealed genetic associations at the ABO, FGG, F11, MYH7B, and HLA-DRA loci. Through our co-analysis we demonstrate further associations with chronic thromboembolic pulmonary hypertension at the F2, TSPAN15, SLC44A2 and F5 loci but find no statistically significant associations shared with idiopathic pulmonary arterial hypertension.

CONCLUSIONS: Chronic thromboembolic pulmonary hypertension is a partially heritable polygenic disease, with related though distinct genetic associations to pulmonary embolism and to deep vein thrombosis.

PMID:38470220 | DOI:10.1164/rccm.202307-1236OC