Structural basis of PETISCO complex assembly during piRNA biogenesis in C. elegans.

Piwi-interacting RNAs (piRNAs) constitute a class of small RNAs that bind PIWI proteins and are essential to repress transposable elements in the animal germline, thereby promoting genome stability and maintaining fertility. C. elegans piRNAs (21U RNAs) are transcribed individually from minigenes as precursors that require 5' and 3' processing. This process depends on the PETISCO complex, consisting of four proteins: IFE-3, TOFU-6, PID-3, and ERH-2. We used biochemical and structural biology approaches to characterize the PETISCO architecture and its interaction with RNA, together with its effector proteins TOST-1 and PID-1. These two proteins define different PETISCO functions: PID-1 governs 21U processing, whereas TOST-1 links PETISCO to an unknown process essential for early embryogenesis. Here, we show that PETISCO forms an octameric assembly with each subunit present in two copies. Determination of structures of the TOFU-6/PID-3 and PID-3/ERH-2 subcomplexes, supported by in vivo studies of subunit interaction mutants, allows us to propose a model for the formation of the TOFU-6/PID-3/ERH-2 core complex and its functionality in germ cells and early embryos. Using NMR spectroscopy, we demonstrate that TOST-1 and PID-1 bind to a common surface on ERH-2, located opposite its PID-3 binding site, explaining how PETISCO can mediate different cellular roles.

Statistical optimization and sequential scale-up of α-galactosidase production by Actinoplanes utahensis B1 from shake flask to pilot scale.

α-Galactosidase (α-GAL) is a class of hydrolase that releases galactose from galacto-oligosaccharides and synthetic substrates such as pNPG. In this study, the production of α-GAL by Actinoplanes utahensis B1 in submerged fermentation was enhanced by using statistical methods. The effects of temperature, pH, and inoculum percentage on enzyme secretion were optimized using BBD of RSM. The optimized process was scaled up from the shake flask to the laboratory scale (5 L) and to pilot scale (30 L) using KLa based scale-up strategy. By using BBD, a maximum yield of 62.5 U/mL was obtained at a temperature of 28 °C, a pH of 6.9, and an inoculum of 6.4%. Scale-up was performed successfully and achieved a yield of 74.4 U/mL and 76.8 U/mL in laboratory scale and pilot scale fermenters. The TOST was performed to validate the scale-up strategy and the results showed a confidence level of 95% for both scales indicating the perfect execution of scale-up procedure. Through the implementation of BBD and scale-up strategy, the overall enzyme yield has been significantly increased to 76%. This is the first article to explore the scale-up of α-GAL from the A. utahensis B1 strain and provide valuable insights for industrial applications.

Controlling the type I error rate in two-stage sequential adaptive designs when testing for average bioequivalence.

In a 2×2 crossover trial for establishing average bioequivalence (ABE) of a generic agent and a currently marketed drug, the recommended approach to hypothesis testing is the two one-sided test (TOST) procedure, which depends, among other things, on the estimated within-subject variability. The power of this procedure, and therefore the sample size required to achieve a minimum power, depends on having a good estimate of this variability. When there is uncertainty, it is advisable to plan the design in two stages, with an interim sample size reestimation after the first stage, using an interim estimate of the within-subject variability. One method and 3 variations of doing this were proposed by Potvin et al. Using simulation, the operating characteristics, including the empirical type I error rate, of the 4 variations (called Methods A, B, C, and D) were assessed by Potvin et al and Methods B and C were recommended. However, none of these 4 variations formally controls the type I error rate of falsely claiming ABE, even though the amount of inflation produced by Method C was considered acceptable. A major disadvantage of assessing type I error rate inflation using simulation is that unless all possible scenarios for the intended design and analysis are investigated, it is impossible to be sure that the type I error rate is controlled. Here, we propose an alternative, principled method of sample size reestimation that is guaranteed to control the type I error rate at any given significance level. This method uses a new version of the inverse-normal combination of p-values test, in conjunction with standard group sequential techniques, that is more robust to large deviations in initial assumptions regarding the variability of the pharmacokinetic endpoints. The sample size reestimation step is based on significance levels and power requirements that are conditional on the first-stage results. This necessitates a discussion and exploitation of the peculiar properties of the power curve of the TOST testing procedure. We illustrate our approach with an example based on a real ABE study and compare the operating characteristics of our proposed method with those of Method B of Povin et al.

Content uniformity testing for stratified samples via parametric tolerance interval testing.

Historically in the biopharmaceutical setting, USP<905> has been used to establish that a batch of drug product has acceptable content uniformity. More recently, alternative approaches such as the two one-sided parametric tolerance interval test (PTI-TOST) have been proposed to establish content uniformity. Traditionally, the PTI-TOST is implemented as a sequential, two-tiered test, under the generally accepted assumption that the data are independently and identically distributed. Since the material is sequenced through the manufacturing process over a period of time, there are conceptually arguable locations within each batch, for instance: beginning, middle, and end. In such a situation, a practitioner may wish to evaluate potential effects of these batch locations, for example, during process validation. If location (stratified) differences exist within the batch and if multiple samples are taken from each location, significant within-location correlations may be induced in the data. In such a case, the traditional PTI-TOST underestimates the total variability, thereby improperly boosting the power of the test method. When there is reason to believe that location variances exist, the batch may be evaluated using stratified sampling, and the location effect may be modeled. In this paper, a two-tiered PTI-TOST that accounts for both between-location and within-location variance components is introduced. Operating characteristic curves and practical advice are given to aid the practitioner's uptake of the proposed method.

Simultaneous confidence regions for multivariate bioequivalence.

Demonstrating bioequivalence of several pharmacokinetic (PK) parameters, such as AUC and Cmax , that are calculated from the same biological sample measurements is in fact a multivariate problem, even though this is neglected by most practitioners and regulatory bodies, who typically settle for separate univariate analyses. We believe, however, that a truly multivariate evaluation of all PK measures simultaneously is clearly more adequate. In this paper, we review methods to construct joint confidence regions around multivariate normal means and investigate their usefulness in simultaneous bioequivalence problems via simulation. Some of them work well for idealised scenarios but break down when faced with real-data challenges such as unknown variance and correlation among the PK parameters. We study the shapes of the confidence regions resulting from different methods, discuss how marginal simultaneous confidence intervals for the individual PK measures can be derived, and illustrate the application to data from a trial on ticlopidine hydrochloride. An R package is available.

Validation of Foot Placement Locations from Ankle Data of a Kinect v2 Sensor.

The Kinect v2 sensor may be a cheap and easy to use sensor to quantify gait in clinical settings, especially when applied in set-ups integrating multiple Kinect sensors to increase the measurement volume. Reliable estimates of foot placement locations are required to quantify spatial gait parameters. This study aimed to systematically evaluate the effects of distance from the sensor, side and step length on estimates of foot placement locations based on Kinect's ankle body points. Subjects (n = 12) performed stepping trials at imposed foot placement locations distanced 2 m or 3 m from the Kinect sensor (distance), for left and right foot placement locations (side), and for five imposed step lengths. Body points' time series of the lower extremities were recorded with a Kinect v2 sensor, placed frontoparallelly on the left side, and a gold-standard motion-registration system. Foot placement locations, step lengths, and stepping accuracies were compared between systems using repeated-measures ANOVAs, agreement statistics and two one-sided t-tests to test equivalence. For the right side at the 2 m distance from the sensor we found significant between-systems differences in foot placement locations and step lengths, and evidence for nonequivalence. This distance by side effect was likely caused by differences in body orientation relative to the Kinect sensor. It can be reduced by using Kinect's higher-dimensional depth data to estimate foot placement locations directly from the foot's point cloud and/or by using smaller inter-sensor distances in the case of a multi-Kinect v2 set-up to estimate foot placement locations at greater distances from the sensor.

Multiplicity adjustments in testing for bioequivalence.

Bioequivalence of two drugs is usually demonstrated by rejecting two one-sided null hypotheses using the two one-sided tests for pharmacokinetic parameters: area under the concentration-time curve (AUC) and maximum concentration (Cmax). By virtue of the intersection-union test, there is no need for multiplicity adjustment in testing the two one-sided null hypotheses within each parameter. However, the decision rule for bioequivalence often requires equivalence to be achieved simultaneously on both parameters that contain four one-sided null hypotheses together; without adjusting for multiplicity, the family wise error rate (FWER) could fail to be controlled at the nominal type-I error rate α. The multiplicity issue for bioequivalence in this regard is scarcely discussed in the literature. To address this issue, we propose two approaches including a closed test procedure that controls FWER for the simultaneous AUC and Cmax bioequivalence and requires no adjustment of the type-I error, and an alpha-adaptive sequential testing (AAST) that controls FWER by pre-specifying the significance level on AUC (α1) and obtaining it for Cmax (α2) adaptively after testing of AUC. While both methods control FWER, the closed test requires testing of eight intersection null hypotheses each at α, and AAST is at times accomplished through a slight deduction in α1 and no deduction in α2 relative to α. The latter considers equivalence reached in AUC a higher importance than that in Cmax. Illustrated with published data, the two approaches, although operate differently, can lead to the same substantive conclusion and are better than a traditional method like Bonferroni adjustment.

Inference of bioequivalence for log-normal distributed data with unspecified variances.

Two drugs are bioequivalent if the ratio of a pharmacokinetic (PK) parameter of two products falls within equivalence margins. The distribution of PK parameters is often assumed to be log-normal, therefore bioequivalence (BE) is usually assessed on the difference of logarithmically transformed PK parameters (δ). In the presence of unspecified variances, test procedures such as two one-sided tests (TOST) use sample estimates for those variances; Bayesian models integrate them out in the posterior distribution. These methods limit our knowledge on the extent that inference about BE is affected by the variability of PK parameters. In this paper, we propose a likelihood approach that retains the unspecified variances in the model and partitions the entire likelihood function into two components: F-statistic function for variances and t-statistic function for δ. Demonstrated with published real-life data, the proposed method not only produces results that are same as TOST and comparable with Bayesian method but also helps identify ranges of variances, which could make the determination of BE more achievable. Our findings manifest the advantages of the proposed method in making inference about the extent that BE is affected by the unspecified variances, which cannot be accomplished either by TOST or Bayesian method.

Equivalence tests for interchangeability based on two one-sided probabilities.

A test treatment is considered to be interchangeable with its reference treatment if they are equivalent and expected to produce the same clinical result in any given patient. To assess interchangeability, FDA Draft Guidance (1999) and Guidance for Industry (2001, 2003) recommend using individual bioequivalence (IBE) and population bioequivalence (PBE) procedures. Chow (1999) and Chow and Liu (1999) gave a discussion on the limitation of the aggregate criteria of the IBE and PBE proposed therein. They mentioned that it is not clear whether IBE or PBE can imply average bioequivalence. Alternative approaches have been proposed to address the weakness of IBE and PBE. Dong et al. (2014) discuss the tolerance interval method and an approximate test for interchangeability defined by a two-sided probability. These tests may not be able to test for the two one-sided tests (TOST) with asymmetric margins around the true mean difference. In addition, the tests of two-sided probability provide no direction when failing the equivalence in interchangeability. Thus, we reexamine the statistical properties of the two one-sided tolerance interval approaches proposed by Tsong and Shen (2007, 2008). In this project, we extend their approach for parallel arms trials and paired/crossover data without the assumption of equal sample sizes and variances. We also develop the exact power function and assess the type I error rate of our proposed approach. In addition, we study the sample size determination based on the interchangeability testing utilizing the tolerance interval method.

Outcome of Intra-articular Injection of Total Stromal Cells and Platelet-Rich Plasma in Primary Knee Osteoarthritis: A Randomized Clinical Trial.

INTRODUCTION:  Mesenchymal stem cell (MSC) therapy appeared promising in knee osteoarthritis (OA). We examined if a single intra-articular (IA) autologous total stromal cells (TSC) and platelet-rich plasma (PRP) injection improved knee pain, physical function, and articular cartilage thickness in knee OA. METHODS:  The study was performed in the physical medicine and rehabilitation department of Bangabandhu Shaikh Mujib Medical University, Dhaka, Bangladesh. Knee OA was diagnosed according to the American College of Rheumatology criteria and randomly assigned to treatment (received TSC and PRP) and control groups. Kallgreen-Lawrance (KL) scoring system was used to grade primary knee OA. The Visual Analogue Scale (VAS, 0-10 cm) for pain, WOMAC (Western Ontario and McMaster Universities Arthritis Index) for physical function, and medial femoral condylar cartilage (MFC) thickness (millimeters) under ultrasonogram (US) were documented and compared between groups before and after treatment. Statistical Package analyzed data for Social Scientists (SPSS 22.0; IBM Corp, Armonk, NY) was used for data analysis. Pre- and post-intervention outcomes were measured using the Wilcoxon-sign test, whereas Mann-Whitney U-test calculated the difference between groups; a p-value <0.05 was considered statistically significant.  Result: In the treatment group, 15 received IA-TSC and PRP preparation, and in the control group, 15 patients received no injection, but quadricep muscle-strengthening exercise. There was no significant difference between groups regarding VAS for pain, WOMAC physical function, and cartilage thickness before starting the treatment and two weeks after intervention. VAS for pain and WOMAC physical function scores improved profoundly in the treatment group after 12 and 24 weeks of intervention; the pain and physical function scores difference between groups was also significant. However, significant mean femoral cartilage thickness was not changed until the end of 24 weeks (U=175.00, p=0.009 two-tailed and U= 130.00, p=0.016 two-tailed, respectively, for right and left knee). CONCLUSION:  Single TSC and PRP injection reduces knee pain and improves physical function and cartilage thickness in knee OA. While pain and physical function improvement happen earlier, cartilage thickness change takes more time.

Statistically Significant versus Practically Relevant Trend in Stability Data.

How to decide whether a statistically significant trend is of practical relevance? In the context of stability data of pharmaceuticals, this publication provides a way forward to use different measures of (method) variability to compare to the observed changes over time. A panel of analytical experts assessed whether statistically significant trends were of practical relevance or not. For different types of assessing variability, recommendations for decision criteria were derived that best matched these assessments, i.e., finding a suited balance between not detecting a relevant trend and between flagging a trend wrongly as relevant. For this purpose, more than 60 data sets from Biosimilar projects of Sandoz/Novartis were leveraged. Hence, this article provides a scientific way to assess whether a statistically significant trend is of practical relevance or not, and a case study is presented and discussed.

Improving Inferences About Null Effects With Bayes Factors and Equivalence Tests.

Researchers often conclude an effect is absent when a null-hypothesis significance test yields a nonsignificant p value. However, it is neither logically nor statistically correct to conclude an effect is absent when a hypothesis test is not significant. We present two methods to evaluate the presence or absence of effects: Equivalence testing (based on frequentist statistics) and Bayes factors (based on Bayesian statistics). In four examples from the gerontology literature, we illustrate different ways to specify alternative models that can be used to reject the presence of a meaningful or predicted effect in hypothesis tests. We provide detailed explanations of how to calculate, report, and interpret Bayes factors and equivalence tests. We also discuss how to design informative studies that can provide support for a null model or for the absence of a meaningful effect. The conceptual differences between Bayes factors and equivalence tests are discussed, and we also note when and why they might lead to similar or different inferences in practice. It is important that researchers are able to falsify predictions or can quantify the support for predicted null effects. Bayes factors and equivalence tests provide useful statistical tools to improve inferences about null effects.

Statistical Considerations on Clinical Efficacy Studies of Biosimilar for PMDA Submission.

In general, similar to FDA and other health authorities, the PMDA requires clinical efficacy study(ies) to evaluate equivalence between a reference biological product and a Biosimilar product for new drug applications. Even if an identical clinical efficacy study is included in both of PMDA and FDA submissions, the coefficients of confidence interval (CI) used for comparison with the equivalence margins could be different between the two submissions (e.g., 95% CI vs. 90% CI). In this article, we will focus on clinical efficacy studies of Biosimilar products and provide an overview of the two one-sided tests (TOST) and the type I error rate for equivalence design. Then, we summarize published PMDA review reports of Biosimilar products in terms of the coefficients of CI and other elements of the primary endpoints, and explain some Japanese guidelines of Biosimilar and Statistics behind the difference between PMDA and FDA submissions. In addition, we discuss how to use statistical methods correctly and efficiently for PMDA submissions.

Functional Proteomics Identifies a PICS Complex Required for piRNA Maturation and Chromosome Segregation.

piRNAs play significant roles in suppressing transposons and nonself nucleic acids, maintaining genome integrity, and defending against viral infections. In C. elegans, piRNA precursors are transcribed in the nucleus and are subjected to a number of processing and maturation steps. The biogenesis of piRNAs is not fully understood. We use functional proteomics in C. elegans and identify a piRNA biogenesis and chromosome segregation (PICS) complex. The PICS complex contains TOFU-6, PID-1, PICS-1, TOST-1, and ERH-2, which exhibit dynamic localization among different subcellular compartments. In the germlines, the PICS complex contains TOFU-6/PICS-1/ERH-2/PID-1, is largely concentrated at the perinuclear granule zone, and engages in piRNA processing. During embryogenesis, the TOFU-6/PICS-1/ERH-2/TOST-1 complex accumulates in the nucleus and plays essential roles in chromosome segregation. The functions of these factors in mediating chromosome segregation are independent of piRNA production. We speculate that differential compositions of PICS factors may help cells coordinate distinct cellular processes.

Equivalent Knee Injury and Osteoarthritis Outcome Scores 12 and 24 Months After Anterior Cruciate Ligament Reconstruction: Results From the Swedish National Knee Ligament Register.

BACKGROUND: It is not clear whether Knee injury and Osteoarthritis Outcome Score (KOOS) results will be different 1 or 2 years after anterior cruciate ligament (ACL) reconstruction. PURPOSE: To investigate within individual patients enrolled in the Swedish National Knee Ligament Register whether there is equivalence between KOOS at 1 and 2 years after primary ACL reconstruction. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: This cohort study was based on data from the Swedish National Knee Ligament Register during the period January 1, 2005, through December 31, 2013. The longitudinal KOOS values for each individual at the 1- and 2-year follow-up evaluations were assessed through the two one-sided test (TOST) procedure with an acceptance criterion of 4. Subset analysis was performed with patients classified by sex, age, graft type, and type of injury (meniscal and/or cartilage injury). RESULTS: A total of 23,952 patients were eligible for analysis after exclusion criteria were applied (10,116 women, 42.2%; 13,836 men, 57.8%). The largest age group was between 16 and 20 years of age (n = 6599; 27.6%). The most common ACL graft was hamstring tendon (n = 22,504; 94.0%), of which the combination of semitendinosus and gracilis was the most common. A total of 7119 patients reported on the KOOS Pain domain at both 1- and 2-year follow-ups, with a mean difference of 0.21 (13.1 SD, 0.16 SE [90% CI, -0.05 to 0.46], P < .001). The same results were found for the other KOOS subscales: symptoms (mean difference -0.54, 14.1 SD, 0.17 SE [90% CI, -0.81 to -0.26], P < .001), activities of daily living (mean difference 0.45, 10.8 SD, 0.13 SE [90% CI, 0.24 to 0.66], P < .001), sports and recreation (mean difference -0.35, 22.7 SD, 0.27 SE [90% CI, -0.79 to 0.09], P < .001), quality of life (mean difference -0.92, 20.0 SD, 0.24 SE [90% CI, -1.31 to -0.53], P < .001), and the combined KOOS-4 score (mean difference -0.41, 14.5 SD, 0.17 SE [90% CI, -0.70 to -0.13], P < .001). Analyses within specific subsets of patients showed equivalent results between the 2 follow-up evaluations. CONCLUSION: Equivalent results within patients were found in KOOS values at 1- and 2-year follow-ups after ACL reconstruction. The finding was consistent across all KOOS subscales and for all evaluated subsets of patients. This result implies that there is no additional value in capturing both 1- and 2-year KOOS outcomes after ACL reconstruction. However, these findings of equivalence at 1- and 2-year endpoints do not alleviate the need for longer follow-up periods.

Carotid intima-media thickness and plaque assessment by trained medical residents: validation and preliminary testing of a training protocol.

BACKGROUND: Training of nonsonographer physicians or staff members is needed to implement carotid intima-media thickness (CIMT) and plaque screening by ultrasound for the assessment of subclinical atherosclerosis. The purpose of this study was to determine the effect of formal training on CIMT assessment and plaque detection by medical residents. METHODS: A medical resident (R1) was trained using an abbreviated American Society of Echocardiography CIMT protocol. CIMT and plaque assessment by R1 were compared against an expert scanner on 60 subjects using a portable US system. A second medical resident (R2) was then trained on the CIMT protocol focusing on plaque visualization after the results of the first phase of the study were analyzed, and the results were compared against an expert on an additional 10 subjects. RESULTS: In the first phase of the study, a total of 106 images (94% interpretable) were available for CIMT and plaque assessment by both R1 and the expert. CIMT measurements were bioequivalent within the limits of ultrasound resolution, with 88% agreement. Variability on plaque presence was high, with only 53% agreement. R2 and the expert each scanned 10 new subjects twice, from whom 40 images were available for interpretation. R2 demonstrated CIMT agreement (93%) comparable with that observed in phase 1 but with greatly improved plaque agreement (100%). Intraobserver variability during phase 2 for both R2 and the expert was extremely low. CONCLUSIONS: Medical residents can undergo rapid training for CIMT measurement and plaque visualization to detect subclinical atherosclerosis compared with an expert.