Real-World Effectiveness of BNT162b2 Against Infection and Severe Diseases in Children and Adolescents.

BACKGROUND: The efficacy of the BNT162b2 vaccine in pediatrics was assessed by randomized trials before the Omicron variant's emergence. The long-term durability of vaccine protection in this population during the Omicron period remains limited. OBJECTIVE: To assess the effectiveness of BNT162b2 in preventing infection and severe diseases with various strains of the SARS-CoV-2 virus in previously uninfected children and adolescents. DESIGN: Comparative effectiveness research accounting for underreported vaccination in 3 study cohorts: adolescents (12 to 20 years) during the Delta phase and children (5 to 11 years) and adolescents (12 to 20 years) during the Omicron phase. SETTING: A national collaboration of pediatric health systems (PEDSnet). PARTICIPANTS: 77 392 adolescents (45 007 vaccinated) during the Delta phase and 111 539 children (50 398 vaccinated) and 56 080 adolescents (21 180 vaccinated) during the Omicron phase. INTERVENTION: First dose of the BNT162b2 vaccine versus no receipt of COVID-19 vaccine. MEASUREMENTS: Outcomes of interest include documented infection, COVID-19 illness severity, admission to an intensive care unit (ICU), and cardiac complications. The effectiveness was reported as (1-relative risk)*100, with confounders balanced via propensity score stratification. RESULTS: During the Delta period, the estimated effectiveness of the BNT162b2 vaccine was 98.4% (95% CI, 98.1% to 98.7%) against documented infection among adolescents, with no statistically significant waning after receipt of the first dose. An analysis of cardiac complications did not suggest a statistically significant difference between vaccinated and unvaccinated groups. During the Omicron period, the effectiveness against documented infection among children was estimated to be 74.3% (CI, 72.2% to 76.2%). Higher levels of effectiveness were seen against moderate or severe COVID-19 (75.5% [CI, 69.0% to 81.0%]) and ICU admission with COVID-19 (84.9% [CI, 64.8% to 93.5%]). Among adolescents, the effectiveness against documented Omicron infection was 85.5% (CI, 83.8% to 87.1%), with 84.8% (CI, 77.3% to 89.9%) against moderate or severe COVID-19, and 91.5% (CI, 69.5% to 97.6%) against ICU admission with COVID-19. The effectiveness of the BNT162b2 vaccine against the Omicron variant declined 4 months after the first dose and then stabilized. The analysis showed a lower risk for cardiac complications in the vaccinated group during the Omicron variant period. LIMITATION: Observational study design and potentially undocumented infection. CONCLUSION: This study suggests that BNT162b2 was effective for various COVID-19-related outcomes in children and adolescents during the Delta and Omicron periods, and there is some evidence of waning effectiveness over time. PRIMARY FUNDING SOURCE: National Institutes of Health.

Identification and exploration of aging-related subtypes and distinctive role of SERPINE1 in heart failure based on single-cell and bulk RNA sequencing data.

Aging is a major risk factor for heart failure (HF) and is the leading cause of death worldwide. Currently, the nature of the relationship between aging and HF is not entirely clear. Herein, this study aimed to explore new diagnostic biomarkers, molecular typing and therapeutic strategies for HF by investigating the biological significance of aging-related genes in HF. A total of 157 differentially expressed genes (DEGs) were screened totally between HF and normal samples, and functional enrichment analysis of DEGs revealed the strong association of HF progression with aging, immune processes and metabolism. Six HF-specific aging-related genes were further identified, and a diagnostic model was developed and validated for good diagnostic efficacy. In addition, we collected blood samples from 10 normal controls and 10 HF patients for RT-qPCR analysis to verify the bioinformation. We also identified two aging-associated subtypes with distinctly different immune infiltration and metabolic microenvironment. Further single-cell sequencing analysis conducted in the study identified SERPINE1 as a key gene in HF. The distinctive role of SERPINE1 fibroblasts was revealed, including three main findings: (I) fibroblasts had a higher proportion and expression of SERPINE1 levels in HF; (II) the ligand-receptor pair MDK-LRP1 made the most contributions in high interactions with other cell types in SERPINE1 fibroblasts; and (III) SERPINE1 fibroblasts were associated with the interaction of extracellular matrix and receptor and may be regulated by the transcription factor EGR1. In conclusion, this study highlights the importance of aging-related genes in diagnosing HF and regulating immune infiltration. We also identified different HF subtypes and a potentially crucial gene, which may provide a better understanding of the molecular-level mechanisms of aging-related HF and aid in developing effective therapeutic strategies.

DAHOS Study: Efficacy of dapagliflozin in treating heart failure with reduced ejection fraction and obstructive sleep apnea syndrome - A 3-month, multicenter, randomized controlled clinical trial.

BACKGROUND: The recent discovery of new therapeutic approaches to heart failure with reduced ejection fraction (HFrEF), including sodium-glucose cotransporter-2 (SGLT-2) inhibitors, as well as improved treatment of co-morbidities has provided much needed help to HFrEF. In addition, dapagliflozin, one of the SGLT-2 inhibitors, serves as a promising candidate in treating obstructive sleep apnea (OSA) of HFrEF patients due to its likely mechanism of countering the pathophysiology of OSA of HFrEF. METHODS: This 3-month multicenter, prospective, randomized controlled trial enrolled participants with left ventricular ejection fraction (LVEF) less than 40% and apnea-hypopnea index (AHI) greater than 15. Participants were randomized into two groups: the treatment group received optimized heart failure treatment and standard-dose dapagliflozin, while the control group only received optimized heart failure treatment. The primary endpoint was the difference in AHI before and after treatment between the two groups. Secondary endpoints included oxygen desaturation index (ODI), minimum oxygen saturation, longest apnea duration, inflammatory factors (CRP, IL-6), quality of life score, and LVEF. RESULTS: A total of 107 patients were included in the final analysis. AHI, LVEF and other baseline data were similar for the dapagliflozin and control groups. After 12 weeks of dapagliflozin treatment, the dapagliflozin group showed significant improvements in sleep parameters including AHI, HI, longest pause time, ODI, time spent with SpO2 < 90%, and average SpO2. Meanwhile, the control group showed no significant changes in sleep parameters, but did demonstrate significant improvements in left ventricular end-diastolic diameter, LVEF, and NT-proBNP levels at 12 weeks. In the experimental group, BMI was significantly reduced, and there were improvements in ESS score, MLHFQ score, and EQ-5D-3L score, as well as significant reductions in CRP and IL-6 levels, while the CRP and IL-6 levels were not improved in the control group. The decrease in LVEF was more significant in the experimental group compared to the control group. There were no significant differences in the magnitude of the decreases between the two groups. CONCLUSIONS: Dapagliflozin may be an effective treatment for heart failure complicated with OSA, and could be considered as a potential new treatment for OSA. (Trial registration  www.chictr.org.cn , ChiCTR2100049834. Registered 10 August 2021).

Leveraging error-prone algorithm-derived phenotypes: Enhancing association studies for risk factors in EHR data.

OBJECTIVES: It has become increasingly common for multiple computable phenotypes from electronic health records (EHR) to be developed for a given phenotype. However, EHR-based association studies often focus on a single phenotype. In this paper, we develop a method aiming to simultaneously make use of multiple EHR-derived phenotypes for reduction of bias due to phenotyping error and improved efficiency of phenotype/exposure associations. MATERIALS AND METHODS: The proposed method combines multiple algorithm-derived phenotypes with a small set of validated outcomes to reduce bias and improve estimation accuracy and efficiency. The performance of our method was evaluated through simulation studies and real-world application to an analysis of colon cancer recurrence using EHR data from Kaiser Permanente Washington. RESULTS: In settings where there was no single surrogate performing uniformly better than all others in terms of both sensitivity and specificity, our method achieved substantial bias reduction compared to using a single algorithm-derived phenotype. Our method also led to higher estimation efficiency by up to 30% compared to an estimator that used only one algorithm-derived phenotype. DISCUSSION: Simulation studies and application to real-world data demonstrated the effectiveness of our method in integrating multiple phenotypes, thereby enhancing bias reduction, statistical accuracy and efficiency. CONCLUSIONS: Our method combines information across multiple surrogates using a statistically efficient seemingly unrelated regression framework. Our method provides a robust alternative to single-surrogate-based bias correction, especially in contexts lacking information on which surrogate is superior.

One-shot distributed algorithms for addressing heterogeneity in competing risks data across clinical sites.

OBJECTIVE: To characterize the interplay between multiple medical conditions across sites and account for the heterogeneity in patient population characteristics across sites within a distributed research network, we develop a one-shot algorithm that can efficiently utilize summary-level data from various institutions. By applying our proposed algorithm to a large pediatric cohort across four national Children's hospitals, we replicated a recently published prospective cohort, the RISK study, and quantified the impact of the risk factors associated with the penetrating or stricturing behaviors of pediatric Crohn's disease (PCD). METHODS: In this study, we introduce the ODACoRH algorithm, a one-shot distributed algorithm designed for the competing risks model with heterogeneity. Our approach considers the variability in baseline hazard functions of multiple endpoints of interest across different sites. To accomplish this, we build a surrogate likelihood function by combining patient-level data from the local site with aggregated data from other external sites. We validated our method through extensive simulation studies and replication of the RISK study to investigate the impact of risk factors on the PCD for adolescents and children from four children's hospitals within the PEDSnet, A National Pediatric Learning Health System. To evaluate our ODACoRH algorithm, we compared results from the ODACoRH algorithms with those from meta-analysis as well as those derived from the pooled data. RESULTS: The ODACoRH algorithm had the smallest relative bias to the gold standard method (-0.2%), outperforming the meta-analysis method (-11.4%). In the PCD association study, the estimated subdistribution hazard ratios obtained through the ODACoRH algorithms are identical on par with the results derived from pooled data, which demonstrates the high reliability of our federated learning algorithms. From a clinical standpoint, the identified risk factors for PCD align well with the RISK study published in the Lancet in 2017 and other published studies, supporting the validity of our findings. CONCLUSION: With the ODACoRH algorithm, we demonstrate the capability of effectively integrating data from multiple sites in a decentralized data setting while accounting for between-site heterogeneity. Importantly, our study reveals several crucial clinical risk factors for PCD that merit further investigations.

Integrating scRNA-seq to explore novel macrophage infiltration-associated biomarkers for diagnosis of heart failure.

OBJECTIVE: Inflammation and immune cells are closely intertwined mechanisms that contribute to the progression of heart failure (HF). Nonetheless, there is a paucity of information regarding the distinct features of dysregulated immune cells and efficient diagnostic biomarkers linked with HF. This study aims to explore diagnostic biomarkers related to immune cells in HF to gain new insights into the underlying molecular mechanisms of HF and to provide novel perspectives for the detection and treatment of HF. METHOD: The CIBERSORT method was employed to quantify 22 types of immune cells in HF and normal subjects from publicly available GEO databases (GSE3586, GSE42955, GSE57338, and GSE79962). Machine learning methods were utilized to screen for important cell types. Single-cell RNA sequencing (GSE145154) was further utilized to identify important cell types and hub genes. WGCNA was employed to screen for immune cell-related genes and ultimately diagnostic models were constructed and evaluated. To validate these predictive results, blood samples were collected from 40 normal controls and 40 HF patients for RT-qPCR analysis. Lastly, key cell clusters were divided into high and low biomarker expression groups to identify transcription factors that may affect biomarkers. RESULTS: The study found a noticeable difference in immune environment between HF and normal subjects. Macrophages were identified as key immune cells by machine learning. Single-cell analysis further showed that macrophages differed dramatically between HF and normal subjects. This study revealed the existence of five subsets of macrophages that have different differentiation states. Based on module genes most relevant to macrophages, macrophage differentiation-related genes (MDRGs), and DEGs in HF and normal subjects from GEO datasets, four genes (CD163, RNASE2, LYVE1, and VSIG4) were identified as valid diagnostic markers for HF. Ultimately, a diagnostic model containing two hub genes was constructed and then validated with a validation dataset and clinical samples. In addition, key transcription factors driving or maintaining the biomarkers expression programs were identified. CONCLUSION: The analytical results and diagnostic model of this study can assist clinicians in identifying high-risk individuals, thereby aiding in guiding treatment decisions for patients with HF.

Food insecurity and binge eating: A systematic review and meta-analysis.

OBJECTIVE: This review synthesized literature on the relationship between food insecurity and binge eating. METHODS: Relevant studies were identified by searching PubMed, CINAHL, PsycINFO, and gray literature from inception to October 2022. Eligible studies included primary research that assessed the relationship between food insecurity and binge eating. Data extraction was performed independently by two reviewers. Pooled odds ratios and 95% confidence intervals (CI) were obtained from random effect models with the R package meta. Analyses were stratified by binge eating versus binge-eating disorder (BED), study type (cross-sectional vs. longitudinal), and age (adults vs. adolescents). RESULTS: We included 24 articles that reported on 20 studies, and 13 articles were included in the meta-analysis. Based on the random effects meta-analysis, the odds of adults in the food insecure group having binge eating were 1.66 (95% CI = 1.42, 1.93) times the odds of adults in the food secure group having binge eating. The odds of adults in the food insecure group having BED were 2.70 (95% CI = 1.47, 4.96) times the odds of adults in the food secure group having BED. Insufficient data were available for a meta-analysis on adolescents or longitudinal relationships. CONCLUSIONS: These findings support that food insecurity is associated with binge eating in adults. There is a need for research to investigate the mechanisms underlying this relationship. Results highlight the importance of screening participants with food insecurity for disordered eating behaviors and vice versa. Future research is needed to examine whether interventions targeting food insecurity may help to mitigate disordered eating behaviors. PUBLIC SIGNIFICANCE: Food insecurity is a common but under-recognized contributor to binge eating. In this article, we systematically reviewed research that has been published on the relationship between food insecurity and binge eating. We found support that food insecurity should be considered in the prevention and treatment of binge eating.

OBJETIVO: Esta revisión sintetizó la literatura sobre la relación entre la inseguridad alimentaria y comer en atracones. MÉTODOS: Los estudios relevantes se identificaron mediante búsquedas en PubMed, CINAHL, PsycINFO y literatura gris desde su inicio hasta octubre de 2022. Los estudios elegibles incluyeron estudios primarios que evaluaron la relación entre la inseguridad alimentaria y los atracones. La extracción de datos fue realizada de forma independiente por 2 revisores. Los odds ratios agrupados y los intervalos de confianza (IC) del 95% se obtuvieron de modelos de efectos aleatorios con el paquete R meta. Los análisis se estratificaron por comer en atracones versus trastorno por atracón (TpA), tipo de estudio (transversal vs longitudinal) y edad (adultos vs adolescentes). RESULTADOS: Se incluyeron 24 artículos que informaron sobre 20 estudios y 13 artículos se incluyeron en el metaanálisis. Según el metaanálisis de efectos aleatorios, las probabilidades de que los adultos en el grupo de inseguridad alimentaria comieran en atracones fue de 1,66 (IC del 95% = 1,42, 1,93) veces las probabilidades de que los adultos en el grupo de seguridad alimentaria comieran en atracones. Las probabilidades de que los adultos en el grupo de inseguridad alimentaria tuvieran TpA fue 2.70 (IC del 95% = 1.47, 4.96) veces las probabilidades de que los adultos en el grupo de seguridad alimentaria tuvieran TpA. No hubo datos suficientes disponibles para un metaanálisis sobre adolescentes o relaciones longitudinales. CONCLUSIONES: Estos hallazgos apoyan que la inseguridad alimentaria está asociada con comer en atracones en adultos. Existe la necesidad de desarrollar investigación para investigar los mecanismos subyacentes a esta relación. Los resultados resaltan la importancia de evaluar a los participantes con inseguridad alimentaria para detectar conductas alimentarias disfuncionales y viceversa. Se necesitan estudios de investigación futuros para examinar si las intervenciones dirigidas a la inseguridad alimentaria pueden ayudar a mitigar los comportamientos alimentarios disfuncionales.

Prevalence and clinical characteristics of sleep-disordered breathing in patients with heart failure of different left ventricular ejection fractions.

PURPOSES: The prevalence of sleep-disordered breathing (SDB) is high in patients with heart failure (HF), while the prevalence of SDB in HF with different left ventricular ejection fractions (LVEF) has rarely been reported. We aimed to explore the prevalence and clinical characteristics of SDB in patients with HF having different LVEF. METHODS: Patients with stable HF were consecutively enrolled. All patients underwent portable overnight cardiorespiratory polygraphy and echocardiography. According to their LVEF, the patients were divided into the HFrEF (HF with reduced EF, EF < 40%), HFmrEF (HF with mid-range EF, 40 ≤ EF < 50), and HFpEF groups (HF with preserved EF, EF ≥ 50%). The prevalence and clinical data of SDB among the 3 groups were then compared. RESULTS: A total of 252 patients, including 134 men, were enrolled in the study. The prevalence of SDB in patients with HF was 70%. Obstructive sleep apnea (OSA) was diagnosed in 48% and central sleep apnea (CSA) in 22%. The prevalence of SDB in the HFrEE, HFmrEF, and HFpEF groups was 86%, 86%, and 62%, respectively (P = 0.001). The prevalence of OSA among the 3 groups was 42%, 47%, and 49%, respectively (P = 0.708), while the prevalence of CSA among the 3 groups was 44%, 40%, and 13% (P < 0.001). Logistic regression analysis revealed that age and BMI were independent risk factors for OSA in patients with HF, while LVEF and smoking were independent risk factors for CSA in patients with HF. Correlational analyses revealed that LVEF was negatively correlated with apnea-hypopnea index (AHI) (r = -0.309, P < 0.001) and central apnea index (CAI) ( r = -0.558, P < 0.001), while there was no significant correlation with obstructive apnea index (OAI). The ROC curve revealed that LVEF could predict the occurrence of CSA and SDB, with AUC = 0.683 (95%CI 0.600-0.767, P < 0.001) and AUC = 0.630 (95%CI 0.559-0.702, P = 0.001), but not of OSA. CONCLUSIONS: SDB was highly common in HF, and the prevalence of SDB was different in HF with different LVEF, mainly due to the difference in cardiac functions. The prevalence and severity of SDB in HFrEF and HFmrEF were significantly higher than those in HFpEF, which was mainly related to the increase in CSA. When HFmrEF was similar to HFrEF in cardiac functions, the prevalence, type, and severity of SDB were similar between the two groups. Changes in LVEF had a significant impact on CAI, but not on OAI. LVEF can predict the occurrence of CSA and SDB to a certain extent.

Effects of chronic intermittent hypoxia on left cardiac function in young and aged mice.

Obstructive sleep apnea (OSA) is an independent risk factor for cardiovascular disease that is characterized by chronic intermittent hypoxia (CIH), and its impact is related to age. This study aims to assess the age-related impact of CIH on cardiac function and to further explore the mechanism. After 8 wk of severe CIH exposure, the hearts of young mice showed slight physiological hypertrophy, decreased diastolic function, and collagen I accumulation but no obvious change in contractile function. However, the contractile function of the hearts of aged mice was severely decreased. CIH exposure promoted the fragmentation of mitochondria in the hearts of aged mice and decreased the mitochondrial membrane potential of cardiomyocytes, but these effects were not observed in young mice exposed to the same conditions. CIH induced significant decreases in basal respiration, maximum respiration, and ATP production in cardiac mitochondria of aged mice compared with those of young mice. The assessment of mitochondrial-related proteins showed that young mouse hearts had upregulated adaptive nuclear respiratory factors (Nrf)1/2 sirtuin (SIRT)1/3 and transcription factor A (TFAM) expression that stabilized mitochondrial function in response to CIH exposure. Aged mouse hearts exhibited maladaptation to CIH exposure, and downregulation of SIRT1 and TFAM expression resulted in mitochondrial dysfunction.

The effect on brain volume in HIV-negative and non-transplant cryptococcal meningitis.

To explore the brain volume (BV) changes of HIV-negative and non-transplant cryptococcal meningitis (CM) in 1 year after initial therapy. Case data were collected from 78 CM patients who underwent magnetic resonance imaging (MRI) scanning at least 3 times in 1-year interval after initial therapy. The assessment of BV was measured by a non-commercial software, uAI Research Portal. Linear mixed model was used to investigate the association between clinical characteristics and the changes in BV. Longitudinal study showed a decrease in total brain volume (-4.65 cm3, P = .005), regional brain volume including white matter (-2.86 cm3, P = .031) and basal ganglia (-0.25 cm3, P = .007), and increase in cerebrospinal fluid (CSF) volume (3.58 cm3, P = .013) in CM patients in 1 year after initial therapy. Ventricular volume in patients with ventriculoperitoneal shunts (VPS) was lower than that in patients without VPS (-7.5 cm3, P < .05). Ventricular volume in patients with post-infectious inflammatory response syndrome (PIIRS) was larger than that in patients without PIIRS (7.1 cm3, P < .01). In addition, temporal lobe atrophy was associated with corticosteroid therapy (-6.8 cm3, P < .01). The present study suggested that brain atrophy, especially regional BV decrease, could happen in HIV-negative and non-transplant CM patients over a 1-year interval.

We investigated the evolution of brain volume changes in different regions among HIV-negative and non-transplant cryptococcal meningitis (CM) patients within 1 year after initial therapy. To assess whether brain atrophy occurs among HIV-negative and non-transplant CM patients.

Effects of sleep apnea hypopnea syndromes on cardiovascular events: a systematic review and meta-analysis.

PURPOSE: Previous studies suggest that sleep apnea hypopnea syndrome (SAHS) is an independent risk factor that contributes to certain cardiovascular events. However, there are studies arguing that patients with SAHS had lower peak troponin levels when suffering cardiovascular events compared to patients without SAHS, which indicates that there may potentially be a protective effect of SAHS. This meta-analysis aimed to assess the impact of SAHS on cardiovascular events. METHODS: Databases were searched for studies that examined cardiac biomarkers or reported angiographic data when patients with SAHS experienced cardiovascular events. The data about peak cardiac biomarkers and angiographic coronary lesion were extracted and then used to compute the pooled standardized mean difference (SMD) and 95% confidence interval (95% CI). RESULTS: Among 26 studies included in the meta-analysis, there was not a definite difference between the SAHS group and the control group for troponins (SMD, 0.05; 95% CI, [- 0.16, 0.26]), creatine kinase (SMD, - 0.08; 95% CI, [- 0.38, 0.22]), and CK-MB (SMD, - 0.11; 95% CI, [- 0.51, 0.29]). However, patients with SAHS revealed worse coronary lesion condition grading via both Gensini score (SMD, 0.63; 95% CI, [0.31, 0.95]) and SYNTAX score (SMD, 0.99; 95% CI, [0.31-1.67]). CONCLUSIONS: Ischemic preconditioning induced by the intermittent hypoxia at the early stage could generate a cardiac protection effect, which would then benefit SAHS patients encountering a major adverse cardiovascular event.

Federated learning algorithms for generalized mixed-effects model (GLMM) on horizontally partitioned data from distributed sources.

OBJECTIVES: This paper developed federated solutions based on two approximation algorithms to achieve federated generalized linear mixed effect models (GLMM). The paper also proposed a solution for numerical errors and singularity issues. And showed the two proposed methods can perform well in revealing the significance of parameter in distributed datasets, comparing to a centralized GLMM algorithm from R package ('lme4') as the baseline model. METHODS: The log-likelihood function of GLMM is approximated by two numerical methods (Laplace approximation and Gaussian Hermite approximation, abbreviated as LA and GH), which supports federated decomposition of GLMM to bring computation to data. To solve the numerical errors and singularity issues, the loss-less estimation of log-sum-exponential trick and the adaptive regularization strategy was used to tackle the problems caused by federated settings. RESULTS: Our proposed method can handle GLMM to accommodate hierarchical data with multiple non-independent levels of observations in a federated setting. The experiment results demonstrate comparable (LA) and superior (GH) performances with simulated and real-world data. CONCLUSION: We modified and compared federated GLMMs with different approximations, which can support researchers in analyzing versatile biomedical data to accommodate mixed effects and address non-independence due to hierarchical structures (i.e., institutes, region, country, etc.).

Simultaneous high p-nitrophenol concentration and nitrogen removal by two-stage membrane biofilm reactor.

P-nitrophenol (PNP) is highly toxic and difficult to degrade, causing great harm to the ecological environment and human health. A two-stage bench-scale membrane biofilm reactor (MBfR) was constructed to treat wastewater containing high concentration of PNP and the generated nitrogen without external organic carbon sources. The two reactors were supplied with oxygen and methane, respectively. O2-MBfR was used for the degradation of PNP and the improvement of wastewater biodegradability. CH4-MBfR was used for the total nitrogen (TN) removal treatment from O2-MBfR effluent. In this experiment, the performance of the two-stage MBfR process was evaluated and optimized by adjusting operational parameters (aeration pressure, HRT, and pH). Under the optimal operation parameters, the removal efficiencies of PNP (100 mg/L) and TN attained 89.70% and 69.24%, respectively, and the removal loads were 0.930 g·m-2·d-1 and 241.42 mg·m-2·d-1, respectively. The reactor was able to accommodate the concentrations of PNP up to 200-400 mg/L, and the reactor reached maximum efficiency throughout the process when the concentration of PNP in the wastewater was 250 mg/L. The removal rates of PNP and TN reached 95.0% and 69.48%, respectively, and the removal loads were 2.37 g·m-2·d-1 and 96.22 mg·m-2·d-1, respectively. This research provides a better solution for multi-MBfR to treat toxic industrial wastewater containing phenol, nitrophenol, and further TN removal, which would not release any air pollutants into the atmosphere.

Prediction of post-vaccination Guillain-Barré syndrome using data from a passive surveillance system.

PURPOSE: Severe adverse events (AEs), such as Guillain-Barré syndrome (GBS) occur rarely after influenza vaccination. We identify highly associated AEs with GBS and develop prediction models for GBS using the US Vaccine Adverse Event Reporting System (VAERS) reports following trivalent influenza vaccination (FLU3). METHODS: This study analyzed 80 059 reports from the US VAERS between 1990 and 2017. Several AEs were identified as highly associated with GBS and were used to develop the prediction model. Some common and mild AEs that were suspected to be underreported when GBS occurred simultaneously were removed from the final model. The analyses were validated using European influenza vaccine AEs data from EudraVigilance. RESULTS: Of the 80 059 reports, 1185 (1.5%) were annotated as GBS related. Twenty-four AEs were identified as having strong association with GBS. The full prediction model, using age, sex, and all 24 AEs achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 85.4% (90% CI: [83.8%, 86.9%]). After excluding the nine (e.g., pruritus, rash, injection site pain) likely underreported AEs, the final AUC became 77.5% (90% CI: [75.5%, 79.6%]). Two hundred and one (0.25%) reports were predicted as of high risk of GBS (predicted probability >25%) and 84 actually developed GBS. CONCLUSION: The prediction performance demonstrated the potential of developing risk-prediction models utilizing the VAERS cohort. Excluding the likely underreported AEs sacrificed some prediction power but made the model more interpretable and feasible. The high absolute risk of even a small number of AE combinations suggests the promise of GBS prediction within the VAERS dataset.

Reducing Bias Due to Outcome Misclassification for Epidemiologic Studies Using EHR-derived Probabilistic Phenotypes.

Epidemiologic studies using electronic health record (EHR)-derived phenotypes as outcomes are subject to bias due to phenotyping error. In the case of dichotomous phenotypes, existing methods for misclassified outcomes can be used to reduce bias. In this article, we present a bias correction approach for EHR-derived probabilistic phenotypes: continuous predicted probabilities of the outcome of interest. This approach makes use of correction factors that can be computed by hand and do not require specialized software. We used simulation studies to investigate the performance of the proposed approach under a variety of scenarios for accuracy of the probabilistic phenotype, strength of the outcome/exposure association, and prevalence of the outcome of interest. Across all scenarios investigated, the proposed approach substantially reduced bias in association parameter estimates relative to a naive approach. We demonstrate the application of this approach to a study of pediatric type 2 diabetes using data from the PEDSnet network of children's hospitals. This straightforward correction factor can substantially reduce bias and improve the validity of EHR-based epidemiology.

Diagnostic accuracy of the PLASMIC score in patients with suspected thrombotic thrombocytopenic purpura: A systematic review and meta-analysis.

BACKGROUND: The PLASMIC score was developed to identify patients with thrombotic microangiopathy who are most likely to have immune thrombotic thrombocytopenic purpura (TTP) and benefit from therapeutic plasma exchange (TPE). PLASMIC scores of 0-4, 5, and 6-7 are said to correspond to low, intermediate, and high probability of TTP, respectively. STUDY DESIGN AND METHODS: We conducted a systematic review and meta-analysis on the diagnostic accuracy of the PLASMIC score in adults with suspected TTP. We evaluated the sensitivity, specificity, positive predictive value, and negative predictive value (NPV) of PLASMIC score thresholds of ≥5 and ≥6. Study quality was appraised using the QUADAS-2 tool. RESULTS: We identified 13 eligible studies, which collectively enrolled 970 patients. The median prevalence of TTP among eligible studies was 35%. The sensitivity and specificity of a PLASMIC score ≥5 was 0.99 (95% confidence interval [CI], 0.91-1.00) and 0.57 (95% CI, 0.41-0.72), respectively. At a prevalence of 35%, the NPV of a PLASMIC score ≥5 was 0.99 (95% CI, 0.92-1.00). A PLASMIC score ≥6 was associated with a sensitivity and specificity of 0.85 (95% CI, 0.67-0.94) and 0.89 (95% CI, 0.81-0.94), respectively. The NPV of a PLASMIC score ≥6 at a prevalence of 35% was 0.92 (95% CI, 0.82-0.97). CONCLUSION: A PLASMIC score threshold of ≥5 is associated with high sensitivity and NPV and may be a useful screening tool for identifying patients who are unlikely to have TTP and do not require TPE, though prospective assessment is required. A PLASMIC score <6 appears to have insufficient sensitivity to rule out TTP and the need for TPE.

Novel glucagon- and OXM-based peptides acting through glucagon and GLP-1 receptors with body weight reduction and anti-diabetic properties.

Oxyntomodulin (OXM) is an endogenous gastrointestinal hormone, which activates both the Glucagon-like peptide-1 receptor (GLP-1R) and the glucagon receptor (GCGR). However, OXM has shortcomings including poor GLP-1R agonism to control glycemia, short half-life and others. Inspired from the sequence relationship between OXM and glucagon, in this study, we introduced different C-terminus residues of GLP-1, exenatide and OXM to glucagon to get a series of hybrid peptides with enhanced GLP-1R activation. The formed glucagon-exenatide hybrid peptide shows higher GLP-1R activation properties than OXM. Then the peptides based on the glucagon-exenatide hybrid peptide were coupled with fatty acid side chains to prolong their half-lives. As a result, the most potent compound 16a could stimulate insulin secretion and maintain blood glucose in normal level for ~42.6 h in diabetic mice. 16a exhibited reduced HbA1c level in diabetic mice, lowered body weight significantly in obesity mice on chronic treatment assay. 16a, combined efficient GCGR/GLP-1R activity, is potential as novel treatment for obesity and diabetes. This finding provides new insights into balancing GLP-1/GCGR potency of glucagon-exenatide hybrid peptide and is helpful for discovery of novel anti-diabetic and bodyweight-reducing drugs.

Plasma Homocysteine Level Is Associated with the Expanded Disability Status Scale in Neuromyelitis Optica Spectrum Disorder.

BACKGROUND AND OBJECTIVE: Plasma homocysteine (Hcy) levels have been investigated among patients with multiple sclerosis (MS). However, the changes in Hcy levels and the association between Hcy levels and inflammatory/immune/cerebrospinal fluid (CSF) parameters in neuromyelitis optica spectrum disorder (NMOSD) patients have not been investigated yet. METHODS: Case data were collected from 97 acute-phase NMOSD patients and 39 stable-phase NMOSD patients. Patients in the acute phase were divided into 2 groups based on the EDSS score with cutoff equal to 4. Hcy levels, immunoglobulins (Ig) A, G, and M, complement 3 and 4, CH50, C-reactive protein, erythrocyte sedimentation rate (ESR), and CSF examination including white blood cells and total protein were determined. RESULTS: No significant differences in Hcy levels are observed between acute-phase and stable-phase NMOSD patients. Hcy and ESR levels were significantly higher in acute-phase NMOSD patients with EDSS score ≥4. Besides, EDSS is positively correlated with Hcy level, ESR, 1/aquaporin-4 titer and Hcy level is negatively correlated with IgM in acute-phase NMOSD patients. CONCLUSION: Elevated plasma Hcy has the potential to affect the pathogenesis or progression of NMOSD.

Comparing drug safety of hepatitis C therapies using post-market data.

BACKGROUND: Hepatitis C affects about 3 % of the world's population. In the United States, about 3.5 million have chronic hepatitis C, and it is the leading cause of liver cancer and the most common indication for liver transplantation. In the last decades, new advances in therapy have substantially increased the cure rate of hepatitis C to more than 95% with the use of antiviral agents. However, drug safety of the new treatments remains one of the major concerns. Data from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and the Electronic Health Record (EHR) systems provide crucial post-market information to evaluate drug safety. Currently, quantitative evidence of drug safety of hepatitis C treatments based on post-market data are still limited, and there is also a lack of a standard statistical procedure to systematically compare drug safety across multiple drugs using FAERS and EHR. METHOD: In this study, we presented a statistical procedure to compare the difference in adverse events (AE) across multiple hepatitis C drugs using data from FAERS and EHR, and to assess the consistency of results from two data bases. Through three major steps, including descriptive comparison, testing for difference among groups, and quantification of association, the proposed method can provide a quantitative comparison on safety of multiple drugs. Specifically, we compared drugs that were approved by FDA to treat hepatitis C before 2011versus those approved after 2013. We used spontaneous AE reports submitted between 2004 to 2015 from FAERS data base and medical records between 1999 to 2015 from the Cerner health facts data base to estimate and compare the rate of AE after drug use. RESULT: We studied 30 most frequently reported AEs after treatment of hepatitis C, comparing the difference between drugs approved before 2011versus those approved after 2013. Our results showed that there was difference in rate of AE between the two groups of treatment. We reported the AEs that have significant statistical difference, and estimate the difference attributable to variation of age and gender between the two groups of drug users. Our findings are consistent with results in existing literature. Moreover, we compared the results obtained from FAERS data and EHR data, and evaluated the consistency of evidence. CONCLUSION: The proposed procedure is a general and standardized pipeline that can be used to compare and visualize drug safety among multiple drugs to support regulatory decision-makings using post-market data. We showed that there was statistically significant difference in AE rates between the new and old therapies for hepatitis C. We showed that both FAERS and EHR contained large information for research of post-market drug safety, but each has its own strength and limitations. Cautions should be taken when combining evidence from the two data resources and there is a need of more sophisticated informatics and statistical tools for evidence synthesis.

Protective effect of sphingosine-1-phosphate for chronic intermittent hypoxia-induced endothelial cell injury.

Intermittent hypoxia (IH) induced by obstructive sleep apnea (OSA) is the key factor in oxidative stress and the concomitant inflammation of endothelial cells (ECs). In recent years, the lipid sphingosine-1-phosphate (S1P) has been reported to probably play a central role in inflammatory diseases. However, its role in IH-induced endothelial injury remains uncertain. In this study, we investigated the IH-induced ECs inflammation and apoptosis, as well as the role of S1P in both. First, human umbilical vein endothelial cells (HUVECs) were treated with IH to explore the mechanism of S1P and S1P microbubbles (S1P-MBs) in HUVECs with altered function. The intracellular reactive oxygen species (ROS) significantly increased after IH treatment, which further resulted in the increased efficiency of cell apoptosis. Following the S1P and S1P-MBs treatments, the lower Bax protein and Cyt c protein levels in HUVECs indicated the protective effects of S1P for CIH-induced ECs injury. The reason may be that the enhanced expression levels of Gα(i) and S1P receptor 1 in S1P and S1P-MBs treatment groups could actively increase intracellular p-Akt and p-eNOS protein levels, which counteract the increased ROS secondary to inflammation from IH. Therefore, the Akt/eNOS signaling pathway induced by S1P may be important in protecting IH-induced ECs injury. Furthermore, the S1P-MBs may be designed as a novel S1P dosage formulation to protect the body from the ECs injuries in the future.