bluuebunny/crossref_metadata_2025_split huggingface dataset:
Latent Profile/Class Analysis Identifying Differentiated Intervention Effects
Authors: Yang Qing , Zhao Amy , Lee Chiyoung , Wang Xiaofei , Vorderstrasse Allison , Wolever Ruth Q. 
Published: April 2022

Background
The randomized clinical trial is generally considered the most rigorous study design for evaluating overall intervention effects. Because of patient heterogeneity, subgroup analysis is often used to identify differential intervention effects. In research of behavioral interventions, such subgroups often depend on a latent construct measured by multiple correlated observed variables.

Objectives
The purpose of this article was to illustrate latent class analysis/latent profile analysis as a helpful tool to characterize latent subgroups, conduct exploratory subgroup analysis, and identify potential differential intervention effects using clinical trial data.

Methods
After reviewing different approaches for subgroup analysis, latent class analysis/latent profile analysis was chosen to identify heterogeneous patient groups based on multiple correlated variables. This approach is superior in this specific scenario because of its ability to control Type I error, assess intersection of multiple moderators, and improve interpretability. We used a case study example to illustrate the process of identifying latent classes as potential moderators based on both clinical and perceived risk scores and then tested the differential effects of health coaching in improving health behavior for patients with elevated risk of developing coronary heart disease.

Results
We identified three classes based on one clinical risk score and four perceived risk measures for individuals with high risk of developing coronary heart disease. Compared to other classes we assessed, individuals in the class with low clinical risk and low perceived risk benefit most from health coaching to improve their physical activity levels.

Discussion
Latent class analysis/latent profile analysis offers a person-centered approach to identifying distinct patient profiles that can be used as moderators for subgroup analysis. This offers tremendous opportunity to identify differential intervention effects in behavioral research.
The CHARISMA Randomized Controlled Trial: A Relationship-Focused Counseling Intervention Integrated Within Oral PrEP Delivery for HIV Prevention Among Women in Johannesburg, South Africa
Authors: Montgomery Elizabeth T. , Roberts Sarah T. , Reddy Krishnaveni , Tolley Elizabeth E. , Hartmann Miriam , Mathebula Florence , Wagner L. Danielle , Lanham Michele , Wilcher Rose , Browne Erica N. , Baeten Jared M. , Palanee-Phillips Thesla 
Published: April 2022

Background:
Consistent use of oral pre-exposure prophylaxis (PrEP) has been a challenge among women, particularly when in relationships with lack of partner support or intimate partner violence (IPV).

Methods:
We conducted a randomized controlled trial (RCT) of an empowerment counseling intervention called “CHARISMA” delivered to women within a PrEP demonstration project in Johannesburg, South Africa. The trial tested the effectiveness of CHARISMA to increase PrEP adherence; decrease social harms and IPV; and improve partnership dynamics (eg, communication, disclosure and support) compared with those who received the standard of care counselling support and referrals. Four hundred seven HIV-seronegative, nonpregnant women aged 18–45 years were enrolled for 6 months of PrEP use, with 203 randomized (1:1) to the intervention. All participants reporting IPV received counseling and referrals that followed the WHO five-step Listen, Inquire, Validate, Enhance Safety, and Support approach.

Results:
This RCT did not identify statistically significant differences between study arms for PrEP adherence or relationship dynamics, with the exception of an increase in PrEP disclosure among intervention arm women. In our study, we cannot determine whether the lack of detectable findings may have been because of lack of intervention effect, strength of standard of care services, low risk in the study population, or other factors.

Conclusions:
Addressing IPV and relationship dynamics remain important factors influencing HIV risk, and addressing these within the context of PrEP delivery is an important synergistic opportunity. CHARISMA was highly acceptable to participants, and further adaptation and testing of the intervention to other populations and settings will augment the evidence base.
Varying Utilization Rates but Superior Outcomes in Liver Transplantation From Hepatitis C−positive Donors in the United States: An Analysis of the OPTN/UNOS Database
Authors: Bekki Yuki , Crismale James F. , Myers Bryan , Schiano Thomas D. , Florman Sander 
Published: April 2022

Background.
Liver transplantation (LT) from hepatitis C virus (HCV)−positive donors [antibody positive (Ab+) or nucleic acid test−positive (NAT+) donors] has been reported to achieve successful outcomes. However, donor and recipient selection has not been well-characterized.

Methods.
Data between 2015 and 2019 were obtained from the United Network for Organ Sharing database. The utilization rates and graft survival among 35 239 potential donors and 23 780 adult LT recipients were reviewed based on donor HCV Ab/NAT status.

Results.
The utilization of Ab+/NAT+ donors was significantly reduced compared with HCV-negative donors (66.4% versus 80.0%, P < 0.001) among donors aged between 40 and 69 y. Recipients of livers from HCV-positive donors had lower laboratory and allocation Model for End-stage Liver Disease scores (both P < 0.001). HCV-positive donors were younger (P < 0.001). Kaplan-Meyer survival curves demonstrated significantly superior 1-y graft survival in recipients of HCV-positive grafts compared with those from HCV-negative grafts (P = 0.004; 97.1% in Ab−/NAT+, 93.9% in Ab+/NAT−, and 93.7% in Ab+/NAT+ versus 91.8% in Ab−/NAT−). Multivariate analysis for 1-y graft survival identified donor age [hazard ratio (HR) = 1.01; 95% confidence interval (CI), 1.00-1.01] and laboratory Model for End-stage Liver Disease score (HR = 1.01; 95% CI, 1.00-1.01) as independent predictors but not donor HCV status: HR 0.77‚ 95% CI, 0.58-1.02 in Ab+/NAT−; HR 0.82‚ 95% CI, 0.66-1.03 in Ab+/NAT+; and HR 0.39‚ 95% CI, 0.10-1.55 in Ab−/NAT+.

Conclusions.
More widespread utilization of HCV-positive donors, especially Ab+/NAT+ donors of age 40–69 y, may expand the donor pool without impairing short-term outcomes after LT.
Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control
Authors: Fasel U. , Kutz J. N. , Brunton B. W. , Brunton S. L. 
Published: April 2022

Sparse model identification enables the discovery of nonlinear dynamical systems purely from data; however, this approach is sensitive to noise, especially in the low-data limit. In this work, we leverage the statistical approach of bootstrap aggregating (bagging) to robustify the sparse identification of the nonlinear dynamics (SINDy) algorithm. First, an ensemble of SINDy models is identified from subsets of limited and noisy data. The aggregate model statistics are then used to produce inclusion probabilities of the candidate functions, which enables uncertainty quantification and probabilistic forecasts. We apply this ensemble-SINDy (E-SINDy) algorithm to several synthetic and real-world datasets and demonstrate substantial improvements to the accuracy and robustness of model discovery from extremely noisy and limited data. For example, E-SINDy uncovers partial differential equations models from data with more than twice as much measurement noise as has been previously reported. Similarly, E-SINDy learns the Lotka Volterra dynamics from remarkably limited data of yearly lynx and hare pelts collected from 1900 to 1920. E-SINDy is computationally efficient, with similar scaling as standard SINDy. Finally, we show that ensemble statistics from E-SINDy can be exploited for active learning and improved model predictive control.
Highly coordinated nationwide massive travel restrictions are central to effective mitigation and control of COVID-19 outbreaks in China
Authors: Chen Xingru , Fu Feng 
Published: April 2022

COVID-19, the disease caused by the novel coronavirus 2019, has caused grave woes across the globe since it was first reported in the epicentre of Wuhan, Hubei, China, in December 2019. The spread of COVID-19 in China has been successfully curtailed by massive travel restrictions that rendered more than 900 million people housebound for more than two months since the lockdown of Wuhan, and elsewhere, on 23 January 2020. Here, we assess the impact of China’s massive lockdowns and travel restrictions reflected by the changes in mobility patterns across and within provinces, before and during the lockdown period. We calibrate movement flow between provinces with an epidemiological compartment model to quantify the effectiveness of lockdowns and reductions in disease transmission. Our analysis demonstrates that the onset and phase of local community transmission in other provinces depends on the cumulative population outflow received from the epicentre Hubei. Moreover, we show that synchronous lockdowns and consequent reduced mobility lag a certain time to elicit an actual impact on suppressing the spread. Such highly coordinated nationwide lockdowns, applied via a top-down approach along with high levels of compliance from the bottom up, are central to mitigating and controlling
early-stage
outbreaks and averting a massive health crisis.
Racial/Ethnic Heterogeneity in Diet of Low-income Adult Women in the United States: Results from National Health and Nutrition Examination Surveys 2011-2018
Authors: Stephenson Briana Joy K. , Willett Walter C. 
Published: April 2022

ABSTRACTBackgroundPoor diet is a major risk factor of cardiovascular and chronic diseases, particularly for low-income women. However, the pathways by which race/ethnicity plays a role in this risk factor have not been fully explored.ObjectiveThis observational study aims to identify dietary consumption differences by race/ethnicity of US women living at or below the 130% poverty income level from 2011-2018.DesignA total of 3005 adult women aged 20-80 years from the National Health and Nutrition Examination Survey (2011-2018) living at or below the 130% poverty-income level with at least one complete 24-hr dietary recall were classified into 5 self-identified racial/ethnic subgroups (Mexican, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, Non-Hispanic Asian). Dietary consumption patterns were defined by 29 major food groups summarized from the Food Pattern Equivalents Database and derived via a robust profile clustering model which identifies foods that share consumption patterns across all low-income adult women, and foods that differ in consumption patterns based on race/ethnic subgroups.ResultsLegumes (protein and vegetable) were the most differentiating foods identified across all racial/ethnic subgroups and were primarily consumed by Mexican and Other Hispanic women. Non-Hispanic Asian women were most likely to favor a high consumption of prudent foods (fruits, vegetables, whole grains). Non-Hispanic White and Black women shared the most similarities in consumption patterns but differed in foods such as milk, poultry, and eggs.ConclusionsDifferences among consumption behaviors of low-income women were found along racial/ethnic lines. Efforts to improve nutritional health of low-income adult women should consider racial/ethnic differences in diet to appropriately focus interventions.DisclaimersN/A.Sources of SupportStudy supported in part by National Heart Lung and Blood Institute (NHLBI) grant R25 (HL105400) to Victor G. Davila-Roman and DC Rao.
Non-intuitive trends of fetal fraction development related to gestational age and fetal gender, and their practical implications for non-invasive prenatal testing
Authors: Forgacova Natalia , Gazdarica Juraj , Budis Jaroslav , Kucharik Marcel , Sekelska Martina , Szemes Tomas 
Published: April 2022

ABSTRACTObjectiveDiscovery of fetal cell-free DNA fragments in maternal blood revolutionized prenatal diagnostics. Although non-invasive prenatal testing (NIPT) is already a matured screening test with high specificity and sensitivity, the accurate estimation of the proportion of fetal fragments, called fetal fraction, is crucial to avoid false-negative results.MethodsWe collected 6999 samples from women undergoing NIPT testing with a single male fetus to demonstrate the influence of fetal fraction by the maternal and fetal characteristics.ResultsWe show several fetal fraction discrepancies that contradict the generally presented conventional view. At first, the fetal fraction is not consistently rising with the maturity of the fetus due to a drop in 15 weeks of maturation. Secondly, the male samples have a lower fetal fraction than female fetuses, arguably due to the smaller gonosomal chromosomes. Finally, we discuss not only the possible reasons why this inconsistency exists but we also outline why these differences have not yet been identified and published.ConclusionWe demonstrate two non-intuitive trends to better comprehend the fetal fraction development and more precise selection of patients with sufficient fetal fraction for accurate testing.Bulleted statementsWhat is already known about this topic?Non-invasive prenatal testing has become a well-known mature screening test, and the fetal fraction is studied in detail by research teams worldwide.What does this study add?Here we demonstrate two non-intuitive trends to better comprehend fetal fraction development that can further increase the sensitivity of routine testing by proper selection of blood sampling according to gestational age and fetus gender.
Plasma multi-omic and cardiac imaging network signatures predict poor long-term outcomes after acute myocardial infarction
Authors: Koh Hiromi W.L. , Pilbrow Anna , Tan Sock Hwee , Zhao Qing , Benke Peter I. , Burla Bo , Torta Federico , Pickering John W. , Troughton Richard , Pemberton Christopher , Soo Wern-Miin , Ling Lieng Hsi , Doughty Robert N. , Choi Hyungwon , Wenk Markus R. , Richards A. Mark , Chan Mark Y. 
Published: April 2022

AbstractBackgroundPrognostic biomarkers for patients admitted for a myocardial infarction (MI) episode are of great interest for risk stratification and follow-up care after discharge. Multi-omics analysis is a standard approach for the discovery of diagnostic and prognostic biomarkers, but few studies have evaluated the prognostic potential of molecular markers in combination with echocardiographic imaging variables.MethodsWe measured the plasma proteome and lipidome in patients discharged from an acute MI and followed for secondary outcomes in New Zealand for a median time of 4.85 years (CDCS, N=741 for network inference, N=464 for predictive analysis) and in Singapore for a median time of 2.0 years (IMMACULATE, N=190 for validation). Using a network-based integrative analysis framework iOmicsPASS+, we mapped proteins, lipids, echocardiographic imaging variables and clinical biomarkers to a unified network and identified predictive subnetwork signatures of major adverse cardiac events (MACE) and heart failure hospitalization (HFH) in CDCS, with validation in IMMACULATE.ResultsSpecific plasma proteins and lipids showed direct connections to cardiac imaging variables in the network. The gold standard biomarker, NT-proBNP, remained one of the best prognostic marker of MACE and HFH, but a number of plasma proteins involved in extracellular matrix organization, chemotaxis, inflammation, and apoptosis were also strong predictors of both outcomes. Hub proteins of subnetwork signatures were enriched in the heart, arteries, kidneys, liver and lungs. BMP10, CAPG, EFEMP1, FSTL3, RSPO4, and RELT were those directly connected to the echocardiographic variables and natriuretic peptides. In particular, EFEMP1 and FSTL3 in combination with diastolic function (E/e’) were strongly predictive of HFH in both CDCS (AUC 0.78, 95%CI 0.72-0.83) and IMMACULATE (AUC 0.72, 0.61-0.84).ConclusionsOur integrative analysis revealed competing signatures beyond established biomarkers of post-MI HFH, comprised of plasma proteins correlated with impaired diastolic function after the primary MI episode.
Blood Draw Site and Analytic Device Influence Hemoglobin Measurements
Authors: Killilea David W. , Kuypers Frans A. , Larkin Sandra K. , Schultz Kathleen 
Published: April 2022

ABSTRACTAnemia is a continuing global public health concern and a priority for international action. The prevalence of anemia is estimated from the hemoglobin (Hb) levels within target populations, yet the procedures for measuring Hb are not standardized and different approaches may result in discrepancies. Several analytical variables have been proposed to influence Hb measurements, but it is difficult to understand the impact on specific variables from large population or field studies. Therefore, we designed a highly controlled protocol that minimized most technical parameters to specifically investigate the impact of blood draw site and analytic device on Hb measurements. A diverse cohort of sixty healthy adults each provided a sequential capillary and venous blood sample that were measured for Hb using an automated hematology analyzer (ADVIA-2120) and two point-of-care devices (HemoCue 201+ and HemoCue 301). Comparing blood draw sites, the mean Hb content was 0.32-0.47 g/dL (2-4%) higher in capillary compared to venous blood from the same donors. Comparing different Hb measuring instruments, the mean Hb content was 0.19-0.46 g/dL (1-4%) higher measured with HemoCue devices compared to ADVIA-2120 in both capillary and venous blood from the same donors. The maximum variance in measurement was also higher with HemoCue devices using blood from venous (5-6% CV) and capillary (21-25% CV) sites compared to ADVIA-2120 (0.6-2% CV). Other variables including blood collection tube manufacturer did not affect mean Hb content. These results demonstrate that even when most technical variables are minimized, the blood draw site and the analytical device can have a small but statistically significant effect on the mean and dispersion of Hb measurements. Even in this study, the few participants identified as mildly anemic using venous blood measured by ADVIA-2120 would not have been classified as anemic using their capillary blood samples or point-of-care analyzers. Thus, caution is warranted when comparing Hb values between studies having differences in blood draw site and Hb measuring device. Future anemia testing should maintain consistency in these analytical variables.
Lowered oxygen saturation and increased body temperature in acute COVID-19 largely predict chronic fatigue syndrome and affective symptoms due to LONG COVID: a precision nomothetic approach
Authors: Al-Hadrawi Dhurgham Shihab , Al-Rubaye Haneen Tahseen , Almulla Abbas F. , Al-Hakeim Hussein Kadhem , Maes Michael 
Published: April 2022

AbstractBackgroundLong coronavirus disease 2019 (LC) is a chronic sequel of acute COVID-19. The exact pathophysiology of the affective, chronic fatigue and physiosomatic symptoms (labeled as “physio-affective phenome”) of LC has remained elusive.ObjectiveThe current study aims to delineate the effects of oxygen saturation (SpO2) and body temperature during the acute phase on the physio-affective phenome of LC.MethodWe recruited 120 LC patients and 36 controls. For all participants, we assessed the lowest SpO2 and peak body temperature during acute COVID-19, and the Hamilton Depression and Anxiety Rating Scale (HAMD/HAMA) and Fibro Fatigue (FF) scales 3 to 4 months later.ResultsLowered SpO2 and increased body temperature during the acute phase and female sex predict 60.7% of the variance in the physio-affective phenome of LC. Using unsupervised learning techniques we were able to delineate a new endophenotype class, which comprises around 26.7% of the LC patients and is characterized by very low SpO2 and very high body temperature, and depression, anxiety, chronic fatigue, and autonomic and gastro-intestinal symptoms scores. Single latent vectors could be extracted from both biomarkers, depression, anxiety and FF symptoms or from both biomarkers, insomnia, chronic fatigue, gastro-intestinal and autonomic symptoms.ConclusionThe newly constructed endophenotype class and pathway phenotypes indicate that the physio-affective phenome of LC is at least in part the consequence of the pathophysiology of acute COVID-19, namely the combined effects of lowered SpO2, increased body temperature and the associated immune-inflammatory processes and lung lesions.
CAPG is required for Ebola virus infection by controlling virus egress from infected cells
Authors: Mori Hiroyuki , Connell James P , Donahue Callie J , Boytz RuthMabel , Patten Justin J , Leung Daisy , LaCount Douglas J , Davey Robert A 
Published: April 2022

AbstractReplication of Ebola virus (EBOV) is dependent upon actin functionality, especially at cell entry through macropinocytosis and at release of virus from cells. Previously, major actin-regulatory factors such as Rac1 and ARP2/3, involved in actin nucleation were shown important in both steps. However, downstream of nucleation, many other cell factors, are needed to control actin dynamics. How these regulate EBOV infection remains largely unknown. Here, we identified the actin-regulating protein, CAPG, as important for EBOV replication. Notably, knockdown (KD) of CAPG specifically inhibited viral infectivity and yield of infectious particles. Mechanistic analysis revealed a requirement of CAPG for virus production from infected cells. Proximity ligation and split GFP reconstitution assays revealed strong association of CAPG with VP40 that was mediated through the S1 domain of CAPG. Overall, CAPG is a novel host factor regulating EBOV infection through connecting actin filament stabilization to viral egress from cells.