Accuracy of Continuous Glucose Monitoring in Hemodialysis Patients With Diabetes.

OBJECTIVE: In the general population, continuous glucose monitoring (CGM) provides convenient and less-invasive glucose measurements than conventional self-monitored blood glucose and results in reduced hypo-/hyperglycemia and increased time-in-target glucose range. However, accuracy of CGM versus blood glucose is not well established in hemodialysis patients. RESEARCH DESIGN AND METHODS: Among 31 maintenance hemodialysis patients with diabetes hospitalized from October 2020-May 2021, we conducted protocolized glucose measurements using Dexcom G6 CGM versus blood glucose, with the latter measured before each meal and at night, plus every 30-min during hemodialysis. We examined CGM-blood glucose correlations and agreement between CGM versus blood glucose using Bland-Altman plots, percentage of agreement, mean and median absolute relative differences (ARDs), and consensus error grids. RESULTS: Pearson and Spearman correlations for averaged CGM versus blood glucose levels were 0.84 and 0.79, respectively; Bland-Altman showed the mean difference between CGM and blood glucose was ∼+15 mg/dL. Agreement rates using %20/20 criteria were 48.7%, 47.2%, and 50.2% during the overall, hemodialysis, and nonhemodialysis periods, respectively. Mean ARD (MARD) was ∼20% across all time periods; median ARD was 19.4% during the overall period and was slightly lower during nonhemodialysis (18.2%) versus hemodialysis periods (22.0%). Consensus error grids showed nearly all CGM values were in clinically acceptable zones A (no harm) and B (unlikely to cause significant harm). CONCLUSIONS: In hemodialysis patients with diabetes, although MARD values were higher than traditional optimal analytic performance thresholds, error grids showed nearly all CGM values were in clinically acceptable zones. Further studies are needed to determine whether CGM improves outcomes in hemodialysis patients.

A single-center, assessor-blinded, randomized controlled clinical trial to test the safety and efficacy of a novel brain-computer interface controlled functional electrical stimulation (BCI-FES) intervention for gait rehabilitation in the chronic stroke population.

BACKGROUND: In the United States, there are over seven million stroke survivors, with many facing gait impairments due to foot drop. This restricts their community ambulation and hinders functional independence, leading to several long-term health complications. Despite the best available physical therapy, gait function is incompletely recovered, and this occurs mainly during the acute phase post-stroke. Therapeutic options are limited currently. Novel therapies based on neurobiological principles have the potential to lead to long-term functional improvements. The Brain-Computer Interface (BCI) controlled Functional Electrical Stimulation (FES) system is one such strategy. It is based on Hebbian principles and has shown promise in early feasibility studies. The current study describes the BCI-FES clinical trial, which examines the safety and efficacy of this system, compared to conventional physical therapy (PT), to improve gait velocity for those with chronic gait impairment post-stroke. The trial also aims to find other secondary factors that may impact or accompany these improvements and establish the potential of Hebbian-based rehabilitation therapies. METHODS: This Phase II clinical trial is a two-arm, randomized, controlled, longitudinal study with 66 stroke participants in the chronic (> 6 months) stage of gait impairment. The participants undergo either BCI-FES paired with PT or dose-matched PT sessions (three times weekly for four weeks). The primary outcome is gait velocity (10-meter walk test), and secondary outcomes include gait endurance, range of motion, strength, sensation, quality of life, and neurophysiological biomarkers. These measures are acquired longitudinally. DISCUSSION: BCI-FES holds promise for gait velocity improvements in stroke patients. This clinical trial will evaluate the safety and efficacy of BCI-FES therapy when compared to dose-matched conventional therapy. The success of this trial will inform the potential utility of a Phase III efficacy trial. TRIAL REGISTRATION: The trial was registered as "BCI-FES Therapy for Stroke Rehabilitation" on February 19, 2020, at clinicaltrials.gov with the identifier NCT04279067.

Variability in Standardized Mortality Rates Among Pediatric Traumatic Brain Injury Patients: A Comparative Analysis of Trauma Centers.

INTRODUCTION: Traumatic brain injury (TBI) causes significant morbidity and mortality in pediatric patients and care is highly variable. Standardized mortality ratio (SMR) summarizes the mortality rate of a specific center relative to the expected rates across all centers, adjusted for case-mix. This study aimed to evaluate variations in SMRs among pediatric trauma centers for TBI. METHODS: Patients aged 1-18 diagnosed with TBI within the National Trauma Data Bank (NTDB) from 2017 to 2019 were included. Center-specific SMRs and 95% confidence intervals identified centers with mortality rates significantly better or worse than the median SMR for all centers. RESULTS: 316 centers with 10,598 patients were included. SMRs were risk-adjusted for patient risk factors. Unadjusted mortality ranged from 16.5 to 29.5%. Three centers (1.5%) had significantly better SMR (SMR <1) and three centers (1.5%) had significantly worse SMR (SMR >1). Significantly better centers had a lower proportion of neurosurgical intervention (2.4% vs. 11.8%, p < 0.001), a higher proportion of supplemental oxygen administration (93.7% vs. 83.5%, p = 0.004) and venous thromboembolism prophylaxis (53.2% vs. 40.6%, p < 0.001) compared to significantly worse centers. CONCLUSIONS: This study identified centers that have significantly higher and lower mortality rates for pediatric TBI patients relative to the overall median rate. These data provide a benchmark for pediatric TBI outcomes and institutional quality improvement. LEVEL OF EVIDENCE: Level III. TYPE OF STUDY: Retrospective Comparative Study.

Temporal trends and racial/ethnic- and sex-differences in LDL cholesterol control among US adults with self-reported atherosclerotic cardiovascular disease.

Objective: Current guidelines for secondary prevention of atherosclerotic cardiovascular disease (ASCVD) recommend targeting a low-density lipoprotein cholesterol (LDL-C) of < 70 mg/dL. However, temporal trends and racial/ethnic- and sex-differences in achievement of LDL-C targets are not well described. We assessed trends and racial/ethnic- and sex-differences in achievement of LDL-C < 70 mg/dL using data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2008 to 2017-March 2020. Methods: We combined NHANES cycles into 4 periods: 2005-2008, 2009-2012, 2013-2016, and 2017-March 2020 and included participants ≥ 40 years with self-reported ASCVD. We estimated LDL-C < 70 mg/dL prevalence over time and further stratified by sex and race/ethnicity. We used multivariable logistic regression adjusted for social determinants of health and clinical covariates to model LDL-C target attainment. Results: Among 1,826 NHANES participants representing 7,161,221 US adults with self-reported ASCVD (59.6% ≥ 65 years, 56.4% male, 74.8% White), LDL-C target attainment increased from 19.0% (95% CI, 15.3%-23.3%) in 2005-2008 to 26.3% (95% CI, 20.4%-33.1%) in 2017-March 2020 (P = 0.012 for trend). Achievement of LDL-C < 70 mg/dL significantly rose among men from19.5% (95% CI, 15.1%-24.8%) to 29.4% (95% CI, 20.7%-29.9%) without significant change in women (from 18.3% [95% CI, 13.6%-24.2%] to 22.5% [95% CI, 13.0%-35.9%]; P = 0.241 for trend). Improvement in LDL-C target attainment was similar among White, Black, and Hispanic individuals (∼5-7% increase) and was greatest among individuals of other (non-White, Hispanic, or Black) race/ethnicity (23.1% increase). In our multivariable analysis, comorbid diabetes and ages 65-75 and > 75 years were associated with LDL-C target attainment. Conclusion: LDL-C control modestly improved between 2005 and 2008 and 2017-March 2020; however, only ∼1/4 of individuals met guideline-directed LDL-C treatment targets by 2017-March 2020. Women had lower LDL-C control and lesser magnitude of improvement in LDL-C control than men, highlighting a need for targeted interventions to improve lipid-lowering therapy utilization in this population.

Computation-aided Design of Rod-Shaped Janus Base Nanopieces for Improved Tissue Penetration and Therapeutics Delivery.

Despite the development of various drug delivery technologies, there remains a significant need for vehicles that can improve targeting and biodistribution in "hard-to-penetrate" tissues. Some solid tumors, for example, are particularly challenging to penetrate due to their dense extracellular matrix (ECM). In this study, we have formulated a new family of rod-shaped delivery vehicles named Janus base nanopieces (Rod JBNps), which are more slender than conventional spherical nanoparticles, such as lipid nanoparticles (LNPs). These JBNp nanorods are formed by bundles of DNA-inspired Janus base nanotubes (JBNts) with intercalated delivery cargoes. To develop this novel family of delivery vehicles, we employed a computation-aided design (CAD) methodology that includes molecular dynamics and response surface methodology. This approach precisely and efficiently guides experimental designs. Using an ovarian cancer model, we demonstrated that JBNps markedly improve penetration into the dense ECM of solid tumors, leading to better treatment outcomes compared to FDA-approved spherical LNP delivery. This study not only successfully developed a rod-shaped delivery vehicle for improved tissue penetration but also established a CAD methodology to effectively guide material design.

Impact of Thyroid Status on Incident Kidney Dysfunction and Chronic Kidney Disease Progression in a Nationally Representative Cohort.

OBJECTIVE: To examine the relationship between thyroid status and incident kidney dysfunction/chronic kidney disease (CKD) progression. PATIENTS AND METHODS: We examined incident thyroid status, ascertained by serum thyrotropin (TSH) levels measured from January 1, 2007, through December 31, 2018, among 4,152,830 patients from the Optum Labs Data Warehouse, containing deidentified retrospective administrative claims data from a large national health insurance plan and electronic health record data from a nationwide network of provider groups. Associations of thyroid status, categorized as hypothyroidism, euthyroidism, or hyperthyroidism (TSH levels >5.0, 0.5-5.0, and <0.5 mIU/L, respectively), with the composite end point of incident kidney dysfunction in patients without baseline kidney dysfunction and CKD progression in those with baseline CKD were examined using Cox models. RESULTS: Patients with hypothyroidism and hyperthyroidism had higher risk of incident kidney dysfunction/CKD progression in expanded case-mix analyses (reference: euthyroidism): adjusted hazard ratios (aHRs) (95% CIs) were 1.37 (1.34 to 1.40) and 1.42 (1.39 to 1.45), respectively. Incrementally higher TSH levels in the upper reference range and TSH ranges for subclinical, mild overt, and overt hypothyroidism (≥3.0-5.0, >5.0-10.0, >10.0-20.0, and >20.0 mIU/L, respectively) were associated with increasingly higher risk of the composite end point (reference: TSH level, 0.5 to <3.0 mIU/L): aHRs (95% CIs) were 1.10 (1.09 to 1.11), 1.37 (1.34 to 1.40), 1.70 (1.59 to 1.83), and 1.70 (1.50 to 1.93), respectively. Incrementally lower TSH levels in the subclinical (<0.5 mIU/L) and overt (<0.1 mIU/L) hyperthyroid ranges were also associated with the composite end point: aHRs (95% CIs) were 1.44 (1.41 to 1.47) and 1.48 (1.39 to 1.59), respectively. CONCLUSION: In a national cohort, TSH levels in the upper reference range or higher (≥3.0 mIU/L) and below the reference range (<0.5 mIU/L) were associated with incident kidney dysfunction/CKD progression.

Electron-Photon Chern Number in Cavity-Embedded 2D Moiré Materials.

We explore theoretically how the topological properties of 2D materials can be manipulated by cavity quantum electromagnetic fields for both resonant and off-resonant electron-photon coupling, with a focus on van der Waals moiré superlattices. We investigate an electron-photon topological Chern number for the cavity-dressed energy minibands that is well defined for any degree of hybridization and entanglement of the electron and photon states. While an off-resonant cavity mode can renormalize electronic topological phases that exist without cavity coupling, we show that when the cavity mode is resonant to electronic miniband transitions, new and higher electron-photon Chern numbers can emerge.

Liquidity creation and bank risk-taking: Evidence from a transition market.

This study contributes to the banking literature by examining the effect of bank liquidity creation on bank risk-taking behaviors in Vietnam - a transition economy. Our data sample comprises 367 observations of 33 Vietnamese commercial banks from 2009 to 2020. We employ the Bias-corrected Least-Squares with Dummy Variables (LSDVC) estimation, which performs better than other dynamic estimators in small and unbalanced panel samples. In this research, bank risk primarily represents non-performing loans (NPLs). Empirical results show that bank liquidity creation significantly reduces NPLs. Otherwise, bank funding diversification significantly increases NPLs in Vietnamese commercial banks. Our findings are robust to alternative measurements of liquidity creation and bank risk. Additionally, we show the moderating role of bank scale in the effects of liquidity creation and funding diversification on bank risk-taking in Vietnamese banks. Our paper is the first research investigating the influence of liquidity creation on bank risk-taking in the specified situation of a transition economy. Besides, it provides empirical evidence to fill the existing research gap. Further, this study provides a list of implications for bank managers and policymakers to manage credit risks and improve the stability of the Vietnamese banking system.

Computational investigation on lipid bilayer disruption induced by amphiphilic Janus nanoparticles: combined effect of Janus balance and charged lipid concentration.

Janus nanoparticles (NPs) with charged/hydrophobic compartments have garnered attention for their potential antimicrobial activity. These NPs have been shown to disrupt lipid bilayers in experimental studies, yet the underlying mechanisms of this disruption at the particle-membrane interface remain unclear. To address this knowledge gap, the present study conducts a computational investigation to systematically examine the disruption of lipid bilayers induced by amphiphilic Janus NPs. The focus of this study is on the combined effects of the hydrophobicity of the Janus NP, referred to as the Janus balance, defined as the ratio of hydrophilic to hydrophobic surface coverage, and the concentration of charged phospholipids on the interactions between Janus NPs and lipid bilayers. Computational simulations were conducted using a coarse-grained molecular dynamics (MD) approach. The results of these MD simulations reveal that while the area change of the bilayer increases monotonically with the Janus balance, the effect of charged lipid concentration in the membrane is not easy to be predicted. Specifically, it was found that the concentration of negatively charged lipids is directly proportional to the intensity of membrane disruption. Conversely, positively charged lipids have a negligible effect on membrane defects. This study provides molecular insights into the significant role of Janus balance in the disruption of lipid bilayers by Janus NPs and supports the selectivity of Janus NPs for negatively charged lipid membranes. Furthermore, the anisotropic properties of Janus NPs were found to play a crucial role in their ability to disrupt the membrane via the combination of hydrophobic and electrostatic interactions. This finding is validated by testing the current Janus NP design on a bacterial membrane-mimicking model. This computational study may serve as a foundation for further studies aimed at optimizing the properties of Janus NPs for specific antimicrobial applications.

Remote gate control of topological transitions in moiré superlattices via cavity vacuum fields.

Placed in cavity resonators with three-dimensionally confined electromagnetic wave, the interaction between quasiparticles in solids can be induced by exchanging virtual cavity photons, which can have a nonlocal characteristic. Here, we investigate the possibility of utilizing this nonlocality to realize the remote control of the topological transition in mesoscopic moiré superlattices at full filling (one electron/hole per supercell) embedded in a split-ring terahertz electromagnetic resonator. We show that gate tuning one moiré superlattice can remotely drive a topological band inversion in another moiré superlattice not in contact but embedded in the same cavity. Our study of remote on/off switching of a topological transition provides a paradigm for the control of material properties via cavity vacuum fields.

Center Volume and Survival Relationship for Neonates With Congenital Diaphragmatic Hernia Treated With Extracorporeal Life Support.

OBJECTIVES: Literature is emerging regarding the role of center volume as an independent variable contributing to improved outcomes. A higher volume of index procedures may be associated with decreased morbidity and mortality. This association has not been examined for the subgroup of infants with congenital diaphragmatic hernia (CDH) receiving extracorporeal life support (ECLS). Our study aims to examine the risk-adjusted association between center volume and outcomes in CDH-ECLS neonates, hypothesizing that higher center volume confers a survival advantage. DESIGN: Multicenter, retrospective comparative study using the Extracorporeal Life Support Organization database. SETTING: One hundred twenty international pediatric centers. PATIENTS: Neonates with CDH managed with ECLS from 2000 to 2019. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The cohort included 4,985 neonates with a mortality rate of 50.6%. For the 120 centers studied, mean center volume was 42.4 ± 34.6 CDH ECLS cases over the 20-year study period. In an adjusted model, higher ECLS volume was associated with lower odds of mortality: odds ratio (OR) 0.995 (95% CI, 0.992-0.999; p = 0.014). For an increase in one sd in volume, that is, 1.75 cases annually, the OR for mortality was lower by 16.7%. Volume was examined as a categorical exposure variable where low-volume centers (fewer than 2 cases/yr) were associated with 54% higher odds of mortality (OR, 1.54; 95% CI, 1.03-2.29) compared with high-volume centers. On-ECLS complications (mechanical, neurologic, cardiac, hematologic metabolic, and renal) were not associated with volume. The likelihood of infectious complications was higher for low- (OR, 1.90; 95% CI, 1.06-3.40) and medium-volume (OR, 1.87; 95% CI, 1.03-3.39) compared with high-volume centers. CONCLUSIONS: In this study, a survival advantage directly proportional to center volume was observed for CDH patients managed with ECLS. There was no significant difference in most complication rates. Future studies should aim to identify factors contributing to the higher mortality and morbidity observed at low-volume centers.

Multivariate spatiotemporal functional principal component analysis for modeling hospitalization and mortality rates in the dialysis population.

Dialysis patients experience frequent hospitalizations and a higher mortality rate compared to other Medicare populations, in whom hospitalizations are a major contributor to morbidity, mortality, and healthcare costs. Patients also typically remain on dialysis for the duration of their lives or until kidney transplantation. Hence, there is growing interest in studying the spatiotemporal trends in the correlated outcomes of hospitalization and mortality among dialysis patients as a function of time starting from transition to dialysis across the United States Utilizing national data from the United States Renal Data System (USRDS), we propose a novel multivariate spatiotemporal functional principal component analysis model to study the joint spatiotemporal patterns of hospitalization and mortality rates among dialysis patients. The proposal is based on a multivariate Karhunen-Loéve expansion that describes leading directions of variation across time and induces spatial correlations among region-specific scores. An efficient estimation procedure is proposed using only univariate principal components decompositions and a Markov Chain Monte Carlo framework for targeting the spatial correlations. The finite sample performance of the proposed method is studied through simulations. Novel applications to the USRDS data highlight hot spots across the United States with higher hospitalization and/or mortality rates and time periods of elevated risk.

Development and Validation of a Prediction Model for Incident Hypothyroidism in a National Chronic Kidney Disease Cohort.

CONTEXT: Hypothyroidism is a common yet under-recognized condition in patients with chronic kidney disease (CKD), which may lead to end-organ complications if left untreated. OBJECTIVE: We developed a prediction tool to identify CKD patients at risk for incident hypothyroidism. METHODS: Among 15 642 patients with stages 4 to 5 CKD without evidence of pre-existing thyroid disease, we developed and validated a risk prediction tool for the development of incident hypothyroidism (defined as thyrotropin [TSH] > 5.0 mIU/L) using the Optum Labs Data Warehouse, which contains de-identified administrative claims, including medical and pharmacy claims and enrollment records for commercial and Medicare Advantage enrollees as well as electronic health record data. Patients were divided into a two-thirds development set and a one-third validation set. Prediction models were developed using Cox models to estimate probability of incident hypothyroidism. RESULTS: There were 1650 (11%) cases of incident hypothyroidism during a median follow-up of 3.4 years. Characteristics associated with hypothyroidism included older age, White race, higher body mass index, low serum albumin, higher baseline TSH, hypertension, congestive heart failure, exposure to iodinated contrast via angiogram or computed tomography scan, and amiodarone use. Model discrimination was good with similar C-statistics in the development and validation datasets: 0.77 (95% CI 0.75-0.78) and 0.76 (95% CI 0.74-0.78), respectively. Model goodness-of-fit tests showed adequate fit in the overall cohort (P = .47) as well as in a subcohort of patients with stage 5 CKD (P = .33). CONCLUSION: In a national cohort of CKD patients, we developed a clinical prediction tool identifying those at risk for incident hypothyroidism to inform prioritized screening, monitoring, and treatment in this population.

Inhaled Nitric Oxide Utilization in Congenital Diaphragmatic Hernia Treated With Extracorporeal Life Support: A Propensity Score Analysis.

Although used commonly, ability of inhaled nitric oxide (iNO) to improve outcomes in infants with congenital diaphragmatic hernia (CDH) who receive extracorporeal life support (ECLS) remains controversial. We sought to determine the association between pre-ECLS use of iNO and mortality in infants with CDH from the Extracorporeal Life Support Organization (ELSO) Registry. Neonates who underwent ECLS for CDH were identified from the ELSO Registry from 2009 to 2019. Patients were categorized into those treated with iNO versus not prior to initiating ECLS. Patients were then matched 1:1 for case-mix based on pre-ECLS covariates using the propensity score (PS) for iNO treatment. The matched groups were compared for mortality. The matched cohorts were also compared for ELSO-defined systems-based complications as secondary outcomes. There were a total of 3,041 infants with an overall mortality of 52.2% and a pre-ECLS iNO use rate of 84.8%. With 1:1 matching, there were 461 infants with iNO use and 461 without iNO use. Following matching, use of iNO was not associated with a difference in mortality (odds ratio [OR] = 0.805; 95% confidence interval [CI], 0.621-1.042; p = 0.114). Results were similar in unadjusted analyses, and after controlling for covariates in the full cohort of patients and in the 1:1 matched data. Patients receiving iNO had significantly higher odds of renal complications (OR = 1.516; 95% CI, 1.141-2.014; p = 0.004), but no other significant differences were observed among secondary outcomes. ECLS use of iNO in CDH patients was not associated with a difference in mortality. Future randomized controlled studies are needed to delineate the utility of iNO in CDH patients.

Impacts of microplastics and heavy metals on the earthworm Eisenia fetida and on soil organic carbon, nitrogen, and phosphorus.

Microplastics (MPs) are increasingly being studied because they have become ubiquitous in aquatic and terrestrial environments. However, little is known about the negative effects of co-contamination by polypropylene microplastic (PP MPs) and heavy metal mixtures on terrestrial environment and biota. This study assessed the adverse effects of co-exposure to PP MPs and heavy metal mixture (Cu2+, Cr6+, and Zn2+) on soil quality and the earthworm Eisenia fetida. Soil samples were collected in the Dong Cao catchment, near Hanoi, Vietnam, and analyzed for changes in extracellular enzyme activity and carbon, nitrogen, and phosphorus availability in the soil. We determined the survival rate of earthworms Eisenia fetida that had ingested MPs and two doses of heavy metals (the environmental level - 1 × - and its double - 2 ×). Earthworm ingestion rates were not significantly impacted by the exposure conditions, but the mortality rate for the 2 × exposure conditions was 100%. Metal-associated PP MPs stimulated the activities of ß-glucosidase, ß-N-acetyl glucosaminidase, and phosphatase enzymes in soil. Principle component analysis showed that these enzymes were positively correlated with Cu2+ and Cr6+ concentrations, but negatively correlated with microbial activity. Zn2+ showed no correlation with soil extracellular enzyme activity or soil microbial activity. Our results showed that co-exposure of earthworms to MPs and heavy metals had no impact on soil nitrogen and phosphorus but caused a decrease in total soil carbon content, with a possible associated risk of increased CO2 emissions.

Novel image analysis tool for rapid screening of cell morphology in preclinical animal models of disease.

The field of cell biology has seen major advances in both cellular imaging modalities and the development of automated image analysis platforms that increase rigor, reproducibility, and throughput for large imaging data sets. However, there remains a need for tools that provide accurate morphometric analysis of single cells with complex, dynamic cytoarchitecture in a high-throughput and unbiased manner. We developed a fully automated image-analysis algorithm to rapidly detect and quantify changes in cellular morphology using microglia cells, an innate immune cell within the central nervous system, as representative of cells that exhibit dynamic and complex cytoarchitectural changes. We used two preclinical animal models that exhibit robust changes in microglia morphology: (1) a rat model of acute organophosphate intoxication, which was used to generate fluorescently labeled images for algorithm development; and (2) a rat model of traumatic brain injury, which was used to validate the algorithm using cells labeled using chromogenic detection methods. All ex vivo brain sections were immunolabeled for IBA-1 using fluorescence or diaminobenzidine (DAB) labeling, images were acquired using a high content imaging system and analyzed using a custom-built algorithm. The exploratory data set revealed eight statistically significant and quantitative morphometric parameters that distinguished between phenotypically distinct groups of microglia. Manual validation of single-cell morphology was strongly correlated with the automated analysis and was further supported by a comparison with traditional stereology methods. Existing image analysis pipelines rely on high-resolution images of individual cells, which limits sample size and is subject to selection bias. However, our fully automated method integrates quantification of morphology and fluorescent/chromogenic signals in images from multiple brain regions acquired using high-content imaging. In summary, our free, customizable image analysis tool provides a high-throughput, unbiased method for accurately detecting and quantifying morphological changes in cells with complex morphologies.

High-Dimensional Fixed Effects Profiling Models and Applications in End-Stage Kidney Disease Patients: Current State and Future Directions.

Profiling analysis aims to evaluate health care providers, including hospitals, nursing homes, or dialysis facilities among others with respect to a patient outcome, such as 30-day unplanned hospital readmission or mortality. Fixed effects (FE) profiling models have been developed over the last decade, motivated by the overall need to (a) improve accurate identification or "flagging" of under-performing providers, (b) relax assumptions inherent in random effects (RE) profiling models, and (c) take into consideration the unique disease characteristics and care/treatment processes of end-stage kidney disease (ESKD) patients on dialysis. In this paper, we review the current state of FE methodologies and their rationale in the ESKD population and illustrate applications in four key areas: profiling dialysis facilities for (1) patient hospitalizations over time (longitudinally) using standardized dynamic readmission ratio (SDRR), (2) identification of dialysis facility characteristics (e.g., staffing level) that contribute to hospital readmission, and (3) adverse recurrent events using standardized event ratio (SER). Also, we examine the operating characteristics with a focus on FE profiling models. Throughout these areas of applications to the ESKD population, we identify challenges for future research in both methodology and clinical studies.

Domain-selective disruption and compression of phase-separated lipid vesicles by amphiphilic Janus nanoparticles.

Janus nanoparticles (NPs) with anisotropic surface functionalities enable unique biomedical applications, but their interaction with the biomembranes cannot be predicted by models derived from nanoparticles with uniform surface chemistry. Here, we combine experiments with molecular dynamics (MD) simulations to investigate the interaction of amphiphilic Janus NPs, which are cationic and hydrophobic on opposite sides, with lipid vesicles exhibiting phase-separated microdomains. We demonstrate that Janus NPs preferentially bind to and extract lipids from liquid-disordered domains over a broad range of vesicle compositions. This domain-selective membrane disruption and the inter-particle attractions concurrently generate a compression force on the vesicle, causing the remaining liquid-ordered domains to bulge and the entire vesicle to wrinkle. The NP-induced membrane compression and deformation are critically driven by the surface anisotropy of the Janus NPs. The findings highlight the feasibility of using the surface anisotropy of NPs to tailor their interactions with different biological membranes.

Dysnatremia and risk of bloodstream infection in dialysis patients.

Background: Emerging data suggest that sodium disarrays including hyponatremia are potential risk factors for infection ensuing from impairments in host immunity, which may be exacerbated by coexisting conditions (i.e. mucosal membrane and cellular edema leading to breakdown of microbial barrier function). While dysnatremia and infection-related mortality are common in dialysis patients, little is known about the association between serum sodium levels and the risk of bloodstream infection in this population. Methods: Among 823 dialysis patients from the national Biospecimen Registry Grant Program who underwent serum sodium testing over the period January 2008-December 2014, we examined the relationship between baseline serum sodium levels and subsequent rate of bloodstream infection. Bloodstream infection events were directly ascertained using laboratory blood culture data. Associations between serum sodium level and the incidence of bloodstream infection were estimated using expanded case mix-adjusted Poisson regression models. Results: In the overall cohort, ∼10% of all patients experienced one or more bloodstream infection events during the follow-up period. Patients with both lower sodium levels <134 mEq/l and higher sodium levels ≥140 mEq/l had higher incident rate ratios (IRRs) of bloodstream infection in expanded case mix analyses (reference 136-<138 mEq/l), with adjusted IRRs of 2.30 [95% confidence interval (CI) 1.19-4.44], 0.77 (95% CI 0.32-1.84), 1.39 (95% CI 0.78-2.47), 1.88 (95% CI 1.08-3.28) and 1.96 (95% CI 1.08-3.55) for sodium levels <134, 134-<136, 138-<140, 140-<142 and ≥142 Eq/l, respectively. Conclusions: Both lower and higher baseline serum sodium levels were associated with a higher rate of subsequent bloodstream infections in dialysis patients. Further studies are needed to determine whether correction of dysnatremia ameliorates infection risk in this population.

A Bayesian multilevel time-varying framework for joint modeling of hospitalization and survival in patients on dialysis.

Over 782 000 individuals in the United States have end-stage kidney disease with about 72% of patients on dialysis, a life-sustaining treatment. Dialysis patients experience high mortality and frequent hospitalizations, at about twice per year. These poor outcomes are exacerbated at key time periods, such as the fragile period after transition to dialysis. In order to study the time-varying effects of modifiable patient and dialysis facility risk factors on hospitalization and mortality, we propose a novel Bayesian multilevel time-varying joint model. Efficient estimation and inference is achieved within the Bayesian framework using Markov chain Monte Carlo, where multilevel (patient- and dialysis facility-level) varying coefficient functions are targeted via Bayesian P-splines. Applications to the United States Renal Data System, a national database which contains data on nearly all patients on dialysis in the United States, highlight significant time-varying effects of patient- and facility-level risk factors on hospitalization risk and mortality. Finite sample performance of the proposed methodology is studied through simulations.