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Background: Low bone mass is common in malnourished patients with chronic kidney disease (CKD) and can lead to a higher risk of fractures. Elderly and CKD patients have the same risk factors for protein-energy wasting, sarcopenia, and osteoporosis. Here, we investigated the association between phase angle (PhA) and bone mineral density (BMD) in dialysis-naïve patients with CKD stage 5 (CKD5) and identified a statistical relationship between PhA and age, which affects bone density. Methods: Bio-impedance spectroscopy for evaluating body composition and PhA and dual-energy X-ray absorptiometry for determining the BMD were simultaneously performed in 167 consecutive patients (mean age, 59.65 ± 13.98 years; women, 40.1%). Two-way analysis of variance (ANOVA) was conducted to assess the potential interaction effect of PhA and age on femoral neck BMD (FN-BMD). Results: Our results showed that PhA and age were independently associated with FN-BMD and T-score in multiple linear regressions analyses. A significant interaction effect of PhA and age on FN-BMD was found on two-way ANOVA (p = 0.028). The average BMD values for the first and second tertiles of the PhA were higher in the young versus elderly group, whereas patients in the elderly group had higher BMD in the third tertiles. Conclusions: A relationship was noted between PhA and BMD in patients with advanced-stage CKD. The effect of PhA level on FN-BMD differed between elderly and young patients. Our study suggested that higher PhA levels could be a marker explaining the maintenance of good bone health in elderly patients with CKD5. Further longitudinal analyses are needed to determine whether PhA predicts the risk of CKD-MBD-related fractures during CKD progression. [ABSTRACT FROM AUTHOR]

Osteopenia, sarcopenia, and increased vascular stiffness are common in patients with chronic kidney disease-mineral bone disorder (CKD-MBD) with protein energy wasting and can lead to worse clinical outcomes. We investigated the potential moderating role of the lean tissue index (LTI) in the relationship between bone microarchitecture and vascular stiffness in dialysis naïve patients with stage 5 CKD. Bioimpedance spectroscopy for evaluating LTI, lumbar spine dual energy X-ray absorptiometry for determining the trabecular bone score (TBS), and arterial applanation tonometry measurements for the central augmentation index, at a heart rate of 75 beats/minute (cAIx75), were simultaneously performed in 117 consecutive patients. A hierarchical regression analysis was conducted to assess the moderating effect of LTI on the relationship between TBS and cAIx75 after adjusting for age and sex. The effect of the interaction between LTI and TBS on cAIx75 was statistically significant (p = 0.030), demonstrating that the cAIx75 tends to decrease more, with the joint effect of LTI and TBS. In the separate analyses, the interaction effect was significant only in women (p = 0.048) and the group of diabetes (p = 0.042). Our study suggests that the evaluation of changes in body composition, bone health, and vascular stiffness needs to be performed simultaneously in patients with advanced-stage CKD. Further research in patients with different stages of CKD warranted to generalize and apply our results to patients in other stages. [ABSTRACT FROM AUTHOR]

For semi‐competing risks data involving a non‐terminal event and a terminal event we derive the asymptotic distributions of the event‐specific win ratios under proportional hazards (PH) assumptions for the relevant cause‐specific hazard functions of the non‐terminal and terminal event, respectively. The win ratios converge to the respective hazard ratios under the PH assumptions and therefore are censoring‐free, whether or not the censoring distributions in the two treatment arms are the same. With the asymptotic bivariate normal distributions of the win ratios, confidence intervals and testing procedures are obtained. Through extensive simulation studies and data analysis, we identified proper transformations of the win ratios that yield good control of the type one error rate for various testing procedures while maintaining competitive power. The confidence intervals also have good coverage probabilities. Furthermore, a test for the PH assumptions and a test of equal hazard ratios are developed. The new procedures are illustrated in the clinical trial Aldosterone Antagonist Therapy for Adults With Heart Failure and Preserved Systolic Function, which evaluated the effects of spironolactone in patients with heart failure and a preserved left ventricular ejection fraction. [ABSTRACT FROM AUTHOR]

Abstract Background Mass spectrometry (MS) data are often generated from various biological or chemical experiments and there may exist outlying observations, which are extreme due to technical reasons. The determination of outlying observations is important in the analysis of replicated MS data because elaborate pre-processing is essential for successful analysis with reliable results and manual outlier detection as one of pre-processing steps is time-consuming. The heterogeneity of variability and low replication are often obstacles to successful analysis, including outlier detection. Existing approaches, which assume constant variability, can generate many false positives (outliers) and/or false negatives (non-outliers). Thus, a more powerful and accurate approach is needed to account for the heterogeneity of variability and low replication. Findings We proposed an outlier detection algorithm using projection and quantile regression in MS data from multiple experiments. The performance of the algorithm and program was demonstrated by using both simulated and real-life data. The projection approach with linear, nonlinear, or nonparametric quantile regression was appropriate in heterogeneous high-throughput data with low replication. Conclusion Various quantile regression approaches combined with projection were proposed for detecting outliers. The choice among linear, nonlinear, and nonparametric regressions is dependent on the degree of heterogeneity of the data. The proposed approach was illustrated with MS data with two or more replicates.

In an infectious disease cohort study, individuals who have been infected with a pathogen are often recruited for follow up. The period between infection and the onset of symptomatic disease, referred to as the incubation period, is of interest because of its importance on disease surveillance and control. However, the incubation period is often difficult to ascertain due to the uncertainty associated with asymptomatic infection onset time. An additional complication is that the observed infected subjects are likely to have longer incubation periods due to the prevalent sampling. In this article, we demonstrate how to estimate the distribution of the incubation period with the uncertain infection onset, subject to left-truncation and right-censoring. We employ a family of sufficiently general parametric models, the generalized odds-rate class of regression models, for the underlying incubation period and its correlation with covariates. In simulation studies, we assess the finite sample performance of the model fitting and hazard function estimation. The proposed method is illustrated on data from the HIV/AIDS study on injection drug users admitted to a detoxification program in Badalona, Spain. [ABSTRACT FROM AUTHOR]

Background: Poor outcomes for patients with ovarian cancer relate to dormant, drug-resistant cancer cells that survive after primary surgery and chemotherapy. Ovarian cancer (OvCa) cells persist in poorly vascularized scars on the peritoneal surface and depend on autophagy to survive nutrient deprivation. The authors have sought drugs that target autophagic cancer cells selectively to eliminate residual disease.Methods: By using unbiased small-interfering RNA (siRNA) screens, the authors observed that knockdown of anaplastic lymphoma kinase (ALK) reduced the survival of autophagic OvCa cells. Small-molecule ALK inhibitors were evaluated for their selective toxicity against autophagic OvCa cell lines and xenografts. Autophagy was induced by reexpression of GTP-binding protein Di-Ras3 (DIRAS3) or serum starvation and was evaluated with Western blot analysis, fluorescence imaging, and transmission electron microscopy. Signaling pathways required for crizotinib-induced apoptosis of autophagic cells were explored with flow cytometric analysis, Western blot analysis, short-hairpin RNA knockdown of autophagic proteins, and small-molecule inhibitors of STAT3 and BCL-2.Results: Induction of autophagy by reexpression of DIRAS3 or serum starvation in multiple OvCa cell lines significantly reduced the 50% inhibitory concentration of crizotinib and other ALK inhibitors. In 2 human OvCa xenograft models, the DIRAS3-expressing tumors treated with crizotinib had significantly decreased tumor burden and long-term survival in 67% to 79% of mice. Crizotinib treatment of autophagic cancer cells further enhanced autophagy and induced autophagy-mediated apoptosis by decreasing phosphorylated STAT3 and BCL-2 signaling.Conclusions: Crizotinib may eliminate dormant, autophagic, drug-resistant OvCa cells that remain after conventional cytoreductive surgery and combination chemotherapy. A clinical trial of ALK inhibitors as maintenance therapy after second-look operations should be seriously considered. [ABSTRACT FROM AUTHOR]

We propose a penalized variable selection method for the Cox proportional hazards model with interval censored data. It conducts a penalized nonparametric maximum likelihood estimation with an adaptive lasso penalty, which can be implemented through a penalized EM algorithm. The method is proven to enjoy the desirable oracle property. We also extend the method to left truncated and interval censored data. Our simulation studies show that the method possesses the oracle property in samples of modest sizes and outperforms available existing approaches in many of the operating characteristics. An application to a dental caries data set illustrates the method's utility. [ABSTRACT FROM AUTHOR]

We propose a semiparametric multi-state frailty model to analyze clustered event-history data subject to interval censoring. The proposed model is motivated by an attempt to study the life course of dental caries at the tooth level, taking into account the multiplicity of caries states and the intra-oral clustering of observations made at periodic time points. Of particular interest is the study of the intra-oral distribution of processes leading to carious lesions, and whether this distribution varies with gender. The model assumes, in view of the covariate profile, a proportionality of the transition intensities conditional on subject-level frailties, coupled with a linear spline approximation of the log baseline intensities. The model estimation is conducted using a penalized likelihood where the smoothing parameters are estimated as reciprocal variance components under a mixed-model representation. A Bayesian method is proposed to predict tooth-level caries transition probabilities, which can be used for tailoring tooth-level caries treatment and prevention plans. Intensive simulation studies indicate that the model fitting and prediction perform reasonably well under realistic sample sizes. The practical utility of the methods is illustrated using data from a longitudinal study on oral health among children from low-income families residing in the city of Detroit, Michigan. [ABSTRACT FROM AUTHOR]

The genetic code sectored via tRNA charging errors, and the code progressed toward closure and universality because of evolution of aminoacyl-tRNA synthetase (aaRS) fidelity and translational fidelity mechanisms. Class I and class II aaRS folds are identified as homologs. From sequence alignments, a structurally conserved Zn-binding domain common to class I and class II aaRS was identified. A model for the class I and class II aaRS alternate folding pathways is posited. Five mechanisms toward code closure are highlighted: 1) aaRS proofreading to remove mischarged amino acids from tRNA; 2) accurate aaRS active site specification of amino acid substrates; 3) aaRS-tRNA anticodon recognition; 4) conformational coupling proofreading of the anticodon-codon interaction; and 5) deamination of tRNA wobble adenine to inosine. In tRNA anticodons there is strong wobble sequence preference that results in a broader spectrum of contacts to synonymous mRNA codon wobble bases. Adenine is excluded from the anticodon wobble position of tRNA unless it is modified to inosine. Uracil is generally preferred to cytosine in the tRNA anticodon wobble position. Because of wobble ambiguity when tRNA reads mRNA, the maximal coding capacity of the three nucleotide code read by tRNA is 31 amino acids + stops. [ABSTRACT FROM AUTHOR]

We advocate for a tRNA- rather than an mRNA-centric model for evolution of the genetic code. The mechanism for evolution of cloverleaf tRNA provides a root sequence for radiation of tRNAs and suggests a simplified understanding of code evolution. To analyze code sectoring, rooted tRNAomes were compared for several archaeal and one bacterial species. Rooting of tRNAome trees reveals conserved structures, indicating how the code was shaped during evolution and suggesting a model for evolution of a LUCA tRNAome tree. We propose the polyglycine hypothesis that the initial product of the genetic code may have been short chain polyglycine to stabilize protocells. In order to describe how anticodons were allotted in evolution, the sectoring-degeneracy hypothesis is proposed. Based on sectoring, a simple stepwise model is developed, in which the code sectors from a 1→4→8→∼16 letter code. At initial stages of code evolution, we posit strong positive selection for wobble base ambiguity, supporting convergence to 4-codon sectors and ∼16 letters. In a later stage, ∼5-6 letters, including stops, were added through innovating at the anticodon wobble position. In archaea and bacteria, tRNA wobble adenine is negatively selected, shrinking the maximum size of the primordial genetic code to 48 anticodons. Because 64 codons are recognized in mRNA, tRNA-mRNA coevolution requires tRNA wobble position ambiguity leading to degeneracy of the code. [ABSTRACT FROM AUTHOR]

Cloverleaf tRNA with a 75 nucleotide (nt) core is posited to have evolved from ligation of three 31 nt minihelices followed by symmetric internal deletions of 9 nt within ligated acceptor stems. Statistical tests strongly support the model. Although the tRNA anticodon loop and T loop are homologs, their U-turns have been treated as distinct motifs. An appropriate comparison, however, shows that intercalation of D loop G19 between T loop bases 4 and 5 causes elevation of T loop base 5 and flipping of T loop bases 6 and 7 out of the 7 nt loop. In the anticodon loop, by contrast, loop bases 3–7 stack tightly to form a stiff connection to mRNA. Furthermore, we identify ancient repeat sequences of 3 (GCG), 5 (UAGCC) and 17 nt (∼CCGGGUUCAAAACCCGG) that comprise 75 out of 75 nts of the tRNA cloverleaf core. To present a sufficiently stiff 3-nt anticodon, a 7-nt anticodon loop was necessary with a U-turn between loop positions 2 and 3. Cloverleaf tRNA, therefore, was a radical evolutionary innovation essential for the 3-nt code. Conservation of GCG and UAGCC repeat sequences indicates that cloverleaf tRNA is at the interface between a strange RNA repeat world and the first evolution of molecules that fold to assume biologic functions. We posit that cloverleaf tRNA was the molecular archetype around which translation systems evolved. [ABSTRACT FROM AUTHOR]

Date Presented 04/20/2023 The study findings suggest that individual efforts to practice a healthy lifestyle could reduce the risk of cognitive frailty. These results can provide a scientific evidence base for policy maker support in health care policy. Primary Author and Speaker: Jihyeun Park Contributing Authors: Daewoo Pak, Ickpyo Hong, Ji-Hyuk Park [ABSTRACT FROM AUTHOR]

Date Presented 04/21/2023 Some physical and mental health variables were identified as important factors of falls among older adults. This study investigated the risk factors that are associated with falls among older adults living alone using machine learning algorithms. Primary Author and Speaker: Suyeong Bae Contributing Authors: Ickpyo Hong, Daewoo Pak [ABSTRACT FROM AUTHOR]

The incubation period of coronavirus disease 2019 (COVID-19) is not always observed exactly due to uncertain onset times of infection and disease symptoms. In this paper, we demonstrate how to estimate the distribution of incubation and its association with patient demographic factors when the exact dates of infection and symptoms' onset may not be observed. The findings from analysis of the confirmed COVID-19 cases indicate that age could be associated with the incubation period, and an age-specific quarantine policy might be more efficient than a unified one in confining COVID-19. [ABSTRACT FROM AUTHOR]

Early detection of ovarian cancer promises to reduce mortality. While serum CA125 can detect more than 60% of patients with early stage (I–II) disease, greater sensitivity might be observed with a panel of biomarkers. Ten protein antigens and 12 autoantibody biomarkers were measured in sera from 76 patients with early stage (I–II), 44 patients with late stage (III–IV) ovarian cancer and 200 healthy participants in the normal risk ovarian cancer screening study. A four-biomarker panel (CA125, osteopontin (OPN), macrophage inhibitory factor (MIF), and anti-IL-8 autoantibodies) detected 82% of early stage cancers compared to 65% with CA125 alone. In early stage subjects the area under the receiver operating characteristic curve (AUC) for the panel (0.985) was significantly greater (p < 0.001) than the AUC for CA125 alone (0.885). Assaying an independent validation set of sera from 71 early stage ovarian cancer patients, 45 late stage patients and 131 healthy women, AUC in early stage disease was improved from 0.947 with CA125 alone to 0.974 with the four-biomarker panel (p = 0.015). Consequently, OPN, MIF and IL-8 autoantibodies can be used in combination with CA125 to distinguish ovarian cancer patients from healthy controls with high sensitivity. Osteopontin appears to be a robust biomarker that deserves further evaluation in combination with CA125. [ABSTRACT FROM AUTHOR]