Tag: statistics

Proteins. 2021 Jun 26. doi: 10.1002/prot.26165. Online ahead of print.

ABSTRACT

Crystallographic B-factors provide direct dynamical information on the internal mobility of proteins that is closely linked to function, and are also widely used as a benchmark in assessing elastic network models. A significant question in the field is: what is the exact amount of thermal vibrations in protein crystallographic B-factors? This work sets out to answer this question. First, we carry out a thorough, statistically sound analysis of crystallographic B-factors of over 10,000 structures. Second, by employing a highly accurate all-atom model based on the well-known CHARMM force field, we obtain computationally the magnitudes of thermal vibrations of nearly 1,000 structures. Our key findings are: (i) the magnitude of thermal vibrations, surprisingly, is nearly protein-independent, as a corollary to the universality for the vibrational spectra of globular proteins established earlier; (ii) the magnitude of thermal vibrations is small, less than 0.1 å² at 100 K; (iii) the percentage of thermal vibrations in B-factors is the lowest at low resolution and low temperature (<10%) but increases to as high as 60% for structures determined at high resolution and at room temperature. The significance of this work is that it provides for the first time, using an extremely large dataset, a thorough analysis of B-factors and their thermal and static disorder components. The results clearly demonstrate that structures determined at high resolution and at room temperature have the richest dynamics information. Since such structures are relatively rare in the PDB database, the work naturally calls for more such structures to be determined experimentally. This article is protected by copyright. All rights reserved.

PMID:34174110 | DOI:10.1002/prot.26165

Genet Epidemiol. 2021 Jun 26. doi: 10.1002/gepi.22419. Online ahead of print.

ABSTRACT

In the analysis of gene expression data, when there are two or more disease conditions/groups (e.g., diseased and normal, responder and nonresponder, and multiple stages/subtypes), differential analysis has been extensively conducted to identify key differences and has important implications. Network analysis takes a system perspective and can be more informative than that limited to simple statistics such as mean and variance. In differential network analysis, a common practice is to first estimate a gene expression network for each condition/group, and then spectral clustering can be applied to the network difference(s) to identify key genes and biological mechanisms that lead to the differences. Compared to “simple” analysis such as regression, differential network analysis can be more challenging with the significantly larger number of parameters. In this study, taking advantage of the increasing popularity of multidimensional profiling data, we develop an assisted analysis strategy and propose incorporating regulator information to improve the identification of key genes (that lead to the differences in gene expression networks). An effective computational algorithm is developed. Comprehensive simulation is conducted, showing that the proposed approach can outperform the benchmark alternatives in identification accuracy. With the The Cancer Genome Atlas lung adenocarcinoma data, we analyze the expressions of genes in the KEGG cell cycle pathway, assisted by copy number variation data. The proposed assisted analysis leads to identification results similar to the alternatives but different estimations. Overall, this study can deliver an efficient and cost-effective way of improving differential network analysis.

PMID:34174112 | DOI:10.1002/gepi.22419

Med Phys. 2021 Jun 26. doi: 10.1002/mp.15054. Online ahead of print.

ABSTRACT

PURPOSE: This study develops a viscous damping model (VDM) based on Rayleigh Damping (RD) with potential use in low cost, non-invasive breast cancer diagnostics using Digital Image Elasto Tomography (DIET).

METHODS: A clinical trial involving 13 subjects, each with a tumor in one breast, resulted in 13 cancerous and 13 healthy breasts. Displacement data following actuator induced steady state vibration in the breast tissue was captured using the DIET system. Over 14,000 reference points on the breast surface were split into four segments and viscous damping constant calculated for each reference point. The VDM was fit to median filtered data for each breast segment and VDM coefficients compared within each breast. One model coefficient, relating to stiffness, was hypothesised to differ in breast segments containing a tumor. Comparison of ‘b’ coefficients in different breast segments using percentage tolerances provided an unbiased, generalizable diagnostic method. Bootstrapping with replacement was used to up-sample the data and create smooth receiver operator characteristic (ROC) curves. A total of 12 breast segmentation configurations were used to demonstrate the robustness of the method.

RESULTS: Fitting the VDM to median filtered data gave consistent results for one VDM coefficient (‘a’) across all breasts. The second VDM coefficient (‘b’) showed diagnostic potential with breast segments having consistent coefficients in healthy breasts. In cancerous breasts ‘b’ coefficients were found to be statistically different in segments containing and adjacent to the tumor compared with the segment furthest from the tumor with p<0.02 using the Student t-Test. Large discrepancies in ‘b’ coefficients were found to be indicative of a tumor with a 14.5% tolerance resulting in sensitivity and specificity of 76.9%. The optimal breast configuration resulted in an area under the ROC curve (AUC) of 0.81 with sensitivity and specificity at 77% and 72%, respectively.

CONCLUSION: This VDM method enables a computationally simple diagnostic technique using DIET for comfortable breast screening for women of all ages. Regular screening potential allows for tolerance alteration based on age, prior subject-specific results, and other risk factors to manage false positives, reducing psychological harm while optimising early detection for successful treatment and decreased mortality.

PMID:34174093 | DOI:10.1002/mp.15054

Biometrics. 2021 Jun 26. doi: 10.1111/biom.13509. Online ahead of print.

ABSTRACT

The COVID-19 pandemic due to the novel coronavirus SARS CoV-2 has inspired remarkable breakthroughs in the development of vaccines against the virus and the launch of several phase 3 vaccine trials in Summer 2020 to evaluate vaccine efficacy (VE). Trials of vaccine candidates using mRNA delivery systems developed by Pfizer-BioNTech and Moderna have shown substantial VEs of 94-95%, leading the US Food and Drug Administration to issue Emergency Use Authorizations and subsequent widespread administration of the vaccines. As the trials continue, a key issue is the possibility that VE may wane over time. Ethical considerations dictate that trial participants be unblinded and those randomized to placebo be offered study vaccine, leading to trial protocol amendments specifying unblinding strategies. Crossover of placebo subjects to vaccine complicates inference on waning of VE. We focus on the particular features of the Moderna trial and propose a statistical framework based on a potential outcomes formulation within which we develop methods for inference on potential waning of VE over time and estimation of VE at any post-vaccination time. The framework clarifies assumptions made regarding individual- and population-level phenomena and acknowledges the possibility that subjects who are more or less likely to become infected may be crossed over to vaccine differentially over time. The principles of the framework can be adapted straightforwardly to other trials. This article is protected by copyright. All rights reserved.

PMID:34174097 | DOI:10.1111/biom.13509

Med Phys. 2021 Jun 26. doi: 10.1002/mp.15057. Online ahead of print.

ABSTRACT

PURPOSE: MR-Linac integrates an MRI scanner and a linear accelerator to provide adaptive radiation treatment. Superior tissue contrast and real-time imaging can give the clinicians confidence to reduce the margins of the planning target volume (PTV). The purpose of this study was to verify the dosimetric accuracy of an MR-Linac system in treating a moving target and assess the error with different motion patterns and adaptation methods.

METHODS: We performed an end-to-end test for Elekta Unity (Elekta, Crawley, UK) using the 4D Dynamic Thorax Phantom (CIRS MRgRT 008Z), comparing the measured and planned dose. The moving phantom had four measurement locations in the tumor, liver, kidney, and spinal cord regions with a PTW30013 ion chamber (Freiberg, Germany). For seven different motion patterns, we first acquired simulation CT using a slow-scanning protocol, based on which we generated reference plans. The treatment technique was the standard intensity-modulated radiation therapy (IMRT). We tested both adaptation workflows: the Adapt-To-Position (ATP) and the Adapt-To-Shape (ATS). The 3D distribution was measured using a diode array phantom (Sun Nuclear Inc., Melbourne, FL) to check the dose distribution accuracy as part of the routine QA process. We also performed end-to-end tests on a conventional Linac. Finally, we used SPSS Statistics 22.0 (Inc., Chicago, IL, USA) for data analysis.

RESULTS: All pre-treatment reference plans and delivered plans had excellent QA results with a better than 95% passing rate of relative Gamma analysis (2%/2 mm criteria). The adaptive planning for MR-Linac produced quality plans. The measured dose in the target agreed with the calculated dose.

CONCLUSIONS: The adaptive treatment on the MR-Linac system investigated met the expected performance with tumor motions. The outline of the target could be visualized and accurately contoured on the 3D MR for online planning. Under different motion patterns, the difference between the measured and calculated dose was acceptable clinically.

PMID:34174099 | DOI:10.1002/mp.15057

Phys Ther. 2021 Jun 25:pzab160. doi: 10.1093/ptj/pzab160. Online ahead of print.

ABSTRACT

OBJECTIVE: Investigate the construct validity and overall appropriateness of test score interpretation of 4 shoulder-related patient-reported outcome (PRO) measures for use in a population of patients with head and neck cancer using Rasch analysis.

METHODS: One hundred eighty-two individuals who had received a neck dissection procedure within the past 2 weeks to 18 months were recruited for this cross-sectional psychometric study. Rasch methodologies were utilized to investigate scale dimensionality, scale hierarchy, response scale structure, and reliability of disability of the arm, shoulder and hand (DASH), QuickDASH, Shoulder Pain and Disability Index (SPADI), and Neck Dissection Impairment Index (NDII).

RESULTS: DASH did not meet criteria for unidimensionality and was deemed inappropriate for utilization in this sample. The QuickDASH, SPADI, and NDII were all determined to be unidimensional. All scales had varying issues with person and item misfit, differential item functioning (DIF), coverage of ability levels, and optimal rating scale requirements. The NDII meets most requirements. All measures were found to meet thresholds for person and item separation as well as reliability statistics.

CONCLUSIONS: Rasch analysis indicates the NDII is the most appropriate measure studied for this population. The QuickDASH and SPADI are recommended with reservation, whereas the DASH is not recommended.

IMPACT: This study demonstrates the use of objective methodologies, using Rasch analysis, to validate PRO recommendations provided by clinical experts in forums such as the Evaluation Database to Guide Effectiveness (EDGE) TaskForce, which are based upon a comprehensive literature review, consideration of published psychometric properties, and expert consensus. Utilization of Rasch methodologies demonstrates weaknesses in this model and provides opportunities to strengthen recommendations for clinicians.

PMID:34174083 | DOI:10.1093/ptj/pzab160

Phys Ther. 2021 Jun 25:pzab162. doi: 10.1093/ptj/pzab162. Online ahead of print.

ABSTRACT

OBJECTIVE: The purpose of this study was to evaluate the effect of exercise training on ectopic fat within skeletal muscle (intermuscular adipose tissue [IMAT]) in adult populations with chronic diseases.

METHODS: A literature search was conducted in relevant databases to identify randomized controlled trials (RCTs) from inception. Selected studies examined the effect of aerobic training (AET), resistance training (RT), or combined training (COM) on IMAT as assessed by noninvasive magnetic resonance (MRI) or computed tomography (CT). Eligibility was determined using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Data extraction was performed using the population (P), intervention (I), comparison (C), outcome (O), timing (T), and settings (S) approach. Methodological quality was analyzed by the Cochrane risk of bias assessment. Standardized effect sizes (ES) with 95% Cis were calculated. Heterogeneity among studies was quantified using I2 statistics. Subgroup and meta-regression analyses were included. Risk of publication bias was examined by the Egger regression test.

RESULTS: Nineteen RCTs included 962 adults (628 women; age range = 34.8-93.4 y) with different chronic conditions that participated in 10 AET, 12 RT, and 5 COM interventions. The quality of studies was deemed moderate. Overall, the effect of exercise on IMAT was small (ES = 0.24; 95% CI = 0.10-0.37; heterogeneity I2 = 0.0%) compared with no exercise or control interventions. Moderate intensity AET and COM had larger ES compared with RT regardless of intensity. This effect was associated with exercise-induced body weight and fat mass losses. Subgroup analysis revealed larger ES in studies assessing IMAT by MRI compared with CT, in adults and middle-aged individuals compared with older adults, and in participants who were HIV+ compared with other diagnoses.

CONCLUSION: AET and COM of moderate intensity reduce IMAT in individuals from 18 to 65 years of age who are affected by chronic diseases. This effect is associated with exercise-induced body weight and fat mass losses. In older individuals who are frail and patients at an advanced disease stage, exercise may result in a paradoxical IMAT accumulation.

IMPACT: In people affected by chronic conditions, IMAT accumulation induces muscle mass and strength losses, decline in physical performance, inflammation, and metabolic alterations. The present study shows that moderate intensity AET or COM prevent or reduce IMAT in these conditions. Thus, the deleterious effect of IMAT on skeletal muscle homeostasis may be reverted by a properly prescribed exercise regime. Findings of the present systematic review are critical for physical therapists and health care professionals as they emphasize the therapeutic role of exercise and provide recommendations for exercise prescription that ultimately may have a positive impact on the course of disease, recovery of functionality, and independence.

LAY SUMMARY: Aerobic exercise (eg, walking/jogging, cycling) alone or combined with resistance exercise (strength training with free-weights, kettle bells, or gym equipment) is effective in reducing fat streaks that infiltrate muscles and impair muscle function and growth, particularly in adults affected by chronic diseases.

PMID:34174085 | DOI:10.1093/ptj/pzab162

J Gastrointestin Liver Dis. 2021 Jun 18;30(2):240-246. doi: 10.15403/jgld-3405.

ABSTRACT

BACKGROUND AND AIMS: Health-related quality of life is an essential part of managing chronically ill patients, including patients with chronic liver disease. Various methods are used to try to assess the quality of life ranging from generic to disease-specific questionnaires. Some of the results may reveal a novel connection to the disease’s evolution, which is observed directly by the patient. This study aimed to validate and assess the chronic liver disease questionnaire (CLDQ-RO) performance in the Romanian population.

METHODS: A two-phase study was designed. The first phase consisted of linguistic validation of CLDQ-RO (translation and piloting), while in the second phase, the questionnaire was applied to patients with various chronic liver diseases. Statistical validation (reliability, structural, and construct validity) was performed using SPSS v20.0, and statistical significance was considered p<0.05.

RESULTS: The CLDQ-RO was applied to 231 patients with chronic liver disease (14.3% with chronic hepatitis, 35.5% with compensated cirrhosis, and 50.2% with decompensated cirrhosis). The questionnaire showed excellent overall reliability (Cronbach’s alpha=0.93) and good structural and construct validity, with most of the items in CLDQ-RO fitting in the domains of the original version of the questionnaire. There was a significant decrease in the overall score of the CLDQ-RO with the progression of disease (p<0.001), indicating a substantial impact of the decompensation event on health-related quality of life. Regarding the type of decompensation, ascites accurately predicted a lower quality of life (p=0.004).

CONCLUSIONS: The CLDQ-RO is a valid and disease-specific method for assessing patients’ health-related quality of life with liver disease. Among the decompensation events, it seems that ascites seriously impacts the quality of life.

PMID:34174063 | DOI:10.15403/jgld-3405

Mil Med. 2021 Jun 26:usab249. doi: 10.1093/milmed/usab249. Online ahead of print.

ABSTRACT

INTRODUCTION: Predictors of deaths of despair, including substance use disorder, psychological distress, and suicidality, are known to be elevated among young adults and recent military veterans. Limited information is available to distinguish age effects from service-era effects. We assessed these effects on indicators of potential for deaths of despair in a large national sample of U.S. adults aged ≥19 years.

MATERIALS AND METHODS: The study was a retrospective, cross-sectional analysis of publicly available data for 2015-2019 from 201,846 respondents to the National Survey on Drug Use and Health (NSDUH), which measures psychological symptoms and substance use behaviors using standardized scales and diagnostic definitions. Indicators of potential for a death of despair included liver cirrhosis, past-year serious suicidal ideation, serious psychological distress per the Kessler-6 scale, and active substance use disorder (e.g., binge drinking on ≥5 occasions in the past month, nonmedical use of prescribed controlled substances, and illicit drug use). Bivariate, age-stratified bivariate, and multivariate logistic regression analyses were performed using statistical software and tests appropriate for the NSDUH complex sampling design. Covariates included demographic characteristics, chronic conditions, and religious service attendance.

RESULTS: Indicators were strongly and consistently age-associated, with ≥1 indicator experienced by 45.5% of respondents aged 19-25 years and 10.7% of those aged ≥65 years (P < .01). After age stratification, service-era effects were modest and occurred only among adults aged ≥35 years. The largest service-associated increase was among adults aged 35-49 years; service beginning or after 1975 was associated (P < .01), with increased prevalence of ≥1 indicator (30.2%-34.2% for veterans and 25.2% for nonveterans) or ≥2 indicators (6.4%-8.2% for veterans and 5.4% for nonveterans). Covariate-adjusted results were similar, with adjusted probabilities of ≥1 indicator declining steadily with increasing age: among those 19-34 years, 39.9% of nonveterans and 42.2% of Persian Gulf/Afghanistan veterans; among those aged ≥65 years, 10.3% of nonveterans, 9.2% of World War II/Korea veterans, and 14.4% of Vietnam veterans.

CONCLUSIONS: After accounting for age, military service-era effects on potential for a death of despair were modest but discernible. Because underlying causes of deaths of despair may vary by service era (e.g., hostility to Vietnam service experienced by older adults versus environmental exposures in the Persian Gulf and Afghanistan), providers treating veterans of different ages should be sensitive to era-related effects. Findings suggest the importance of querying for symptoms of mental distress and actively engaging affected individuals, veteran or nonveteran, in appropriate treatment to prevent deaths of despair.

PMID:34174076 | DOI:10.1093/milmed/usab249

Sci Rep. 2021 Jun 25;11(1):13323. doi: 10.1038/s41598-021-92725-8.

ABSTRACT

Lung cancer is one of the deadliest cancers in the world. Two of the most common subtypes, lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), have drastically different biological signatures, yet they are often treated similarly and classified together as non-small cell lung cancer (NSCLC). LUAD and LUSC biomarkers are scarce, and their distinct biological mechanisms have yet to be elucidated. To detect biologically relevant markers, many studies have attempted to improve traditional machine learning algorithms or develop novel algorithms for biomarker discovery. However, few have used overlapping machine learning or feature selection methods for cancer classification, biomarker identification, or gene expression analysis. This study proposes to use overlapping traditional feature selection or feature reduction techniques for cancer classification and biomarker discovery. The genes selected by the overlapping method were then verified using random forest. The classification statistics of the overlapping method were compared to those of the traditional feature selection methods. The identified biomarkers were validated in an external dataset using AUC and ROC analysis. Gene expression analysis was then performed to further investigate biological differences between LUAD and LUSC. Overall, our method achieved classification results comparable to, if not better than, the traditional algorithms. It also identified multiple known biomarkers, and five potentially novel biomarkers with high discriminating values between LUAD and LUSC. Many of the biomarkers also exhibit significant prognostic potential, particularly in LUAD. Our study also unraveled distinct biological pathways between LUAD and LUSC.

PMID:34172784 | DOI:10.1038/s41598-021-92725-8