Effect of pooled tracheal sample testing on the probability of Mycoplasma hyopneumoniae detection.

Tracheal pooling for Mycoplasma hyopneumoniae (M. hyopneumoniae) DNA detection allows for decreased diagnostic cost, one of the main constraints in surveillance programs. The objectives of this study were to estimate the sensitivity of pooled-sample testing for the detection of M. hyopneumoniae in tracheal samples and to develop probability of M. hyopneumoniae detection estimates for tracheal samples pooled by 3, 5, and 10. A total of 48 M. hyopneumoniae PCR-positive field samples were pooled 3-, 5-, and 10-times using field M. hyopneumoniae DNA-negative samples and tested in triplicate. The sensitivity was estimated at 0.96 (95% credible interval [Cred. Int.]: 0.93, 0.98) for pools of 3, 0.95 (95% Cred. Int: 0.92, 0.98) for pools of 5, and 0.93 (95% Cred. Int.: 0.89, 0.96) for pools of 10. All pool sizes resulted in PCR-positive if the individual tracheal sample Ct value was < 33. Additionally, there was no significant decrease in the probability of detecting at least one M. hyopneumoniae-infected pig given any pool size (3, 5, or 10) of tracheal swabs. Furthermore, this manuscript applies the probability of detection estimates to various real-life diagnostic testing scenarios. Combining increased total animals sampled with pooling can be a cost-effective tool to maximize the performance of M. hyopneumoniae surveillance programs.

A Low Eosinophil to Platelet Ratio as a Worse Prognostic Index for Emergency Department Attendance in Acute Exacerbation of COPD.

Purpose: Identifying prognosis for patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is challenging. Eosinophils and platelet are involved in the development of COPD, which may predict adverse events. The objective of this study was to determine the effect of the eosinophil to platelet ratio (EPR) in predicting adverse events in patients with AECOPD who visited the emergency department. Patients and Methods: The records of patients with AECOPD treated at Dalian Municipal Friendship Hospital from January 2018 to December 2020 were retrospectively reviewed. The relationship between the clinical characteristics and EPR, as cut-off value of 0.755, was evaluated. Results: A total of 508 patients with an AECOPD (316 male, 192 female) were included. An optimal AUC cutoff of 0.755 for the EPR segregated the patients into 2 groups with significantly different mortality (25.3% vs 5.5%, P < 0.001). The same mortality risk with lower EPR was observed among the patients with emergency room attendance (35.6% vs 11.1%, P < 0.001). A model including EPR <0.755, exacerbation history, PaO2 <60mmHg, PaCO2 >50 mm Hg, hypoalbuminemia and age ≥80 was developed to predict death risk and showed good performance. Conclusion: During severe COPD exacerbation, an EPR < 0.755 preceding therapy can predict worse outcomes in patients with an AECOPD.

Using information from network meta-analyses to optimize the power and sample allocation of a subsequent trial with a new treatment.

BACKGROUND: A critical step in trial design is determining the sample size and sample allocation to ensure the proposed study has sufficient power to test the hypothesis of interest: superiority, equivalence, or non-inferiority. When data are available from prior trials and leveraged with the new trial to answer the scientific questions, the value of society's investment in prior research is increased. When prior information is available, the trial design including the sample size and allocation should be adapted accordingly, yet the current approach to trial design does not utilize such information. Ensuring we maximize the value of prior research is essential as there are always constraints on resources, either physical or financial, and designing a trial with adequate power can be a challenge. METHODS: We propose an approach to increasing the power of a new trial by incorporating evidence from a network meta-analysis into the new trial design and analysis. We illustrate the methodology through an example network meta-analysis, where the goal is to identify the optimal allocation ratio for the new three-arm trial, which involves the reference treatment, the new treatment, and the negative control. The primary goal of the new trial is to show that the new treatment is non-inferior to the reference treatment. It may also be of interest to know if the new treatment is superior to the negative control. We propose an optimal treatment allocation strategy which is derived from minimizing the standard error of the log odds ratio estimate of the comparison of interest. We conducted a simulation study to assess the proposed methods to design a new trial while borrowing information from the existing network meta-analysis and compare it to even allocation methods. RESULTS: Using mathematical derivation and simulations, we document that our proposed approach can borrow information from a network meta-analysis to modify the treatment allocation ratio and increase the power of the new trial given a fixed total sample size or to reduce the total sample size needed to reach a desired power. CONCLUSIONS: When prior evidence about the hypotheses of interest is available, the traditional equal allocation strategy is not the most powerful approach anymore. Our proposed methodology can improve the power of trial design, reduce the cost of trials, and maximize the utility of prior investments in research.

Performance experiments with a gas wave ejector equipped with curved channels and an analysis of the influence of channel angles.

Gas wave ejectors (GWEs) utilize pressure waves to efficiently transfer energy between gases, and they have broad applications in the chemical industry. In order to improve the performance of GWEs, the influence of bending angles on GWE performance was studied and experiments involving a GWE equipped with curved channels were carried out for the first time in this study. The research results show that when the exhaust angle difference (φ dout) is ≤-3.9° and the incident angle difference (φ din) is >5.0° or ≤-5.0°, the equipment performance decreases with an increase in the absolute values of the angle differences. The maximum efficiency of the backward-curved-channel device is 61.6% within the experimental range. The experimental efficiency of the curved-channel device and the static-pressure proportion of the total pressure of the medium-pressure gas are enhanced in comparison with a traditional straight-channel device, and the operating power consumption is relatively reduced. Due to the difference between the gas incident and exhaust angles, the manner in which the performance of the curved-channel device varies with the rotation speed is different depending on the working conditions.

Source Data-Absent Unsupervised Domain Adaptation Through Hypothesis Transfer and Labeling Transfer.

Unsupervised domain adaptation (UDA) aims to transfer knowledge from a related but different well-labeled source domain to a new unlabeled target domain. Most existing UDA methods require access to the source data, and thus are not applicable when the data are confidential and not shareable due to privacy concerns. This paper aims to tackle a realistic setting with only a classification model available trained over, instead of accessing to, the source data. To effectively utilize the source model for adaptation, we propose a novel approach called Source HypOthesis Transfer (SHOT), which learns the feature extraction module for the target domain by fitting the target data features to the frozen source classification module (representing classification hypothesis). Specifically, SHOT exploits both information maximization and self-supervised learning for the feature extraction module learning to ensure the target features are implicitly aligned with the features of unseen source data via the same hypothesis. Furthermore, we propose a new labeling transfer strategy, which separates the target data into two splits based on the confidence of predictions (labeling information), and then employ semi-supervised learning to improve the accuracy of less-confident predictions in the target domain. We denote labeling transfer as SHOT++ if the predictions are obtained by SHOT. Extensive experiments on both digit classification and object recognition tasks show that SHOT and SHOT++ achieve results surpassing or comparable to the state-of-the-arts, demonstrating the effectiveness of our approaches for various visual domain adaptation problems. Code will be available at https://github.com/tim-learn/SHOT-plus.

A likelihood ratio test for the homogeneity of between-study variance in network meta-analysis.

BACKGROUND: Network meta-analysis (NMA) is a statistical method used to combine results from several clinical trials and simultaneously compare multiple treatments using direct and indirect evidence. Statistical heterogeneity is a characteristic describing the variability in the intervention effects being evaluated in the different studies in network meta-analysis. One approach to dealing with statistical heterogeneity is to perform a random effects network meta-analysis that incorporates a between-study variance into the statistical model. A common assumption in the random effects model for network meta-analysis is the homogeneity of between-study variance across all interventions. However, there are applications of NMA where the single between-study assumption is potentially incorrect and instead the model should incorporate more than one between-study variances. METHODS: In this paper, we develop an approach to testing the homogeneity of between-study variance assumption based on a likelihood ratio test. A simulation study was conducted to assess the type I error and power of the proposed test. This method is then applied to a network meta-analysis of antibiotic treatments for Bovine respiratory disease (BRD). RESULTS: The type I error rate was well controlled in the Monte Carlo simulation. We found statistical evidence (p value = 0.052) against the homogeneous between-study variance assumption in the network meta-analysis BRD. The point estimate and confidence interval of relative effect sizes are strongly influenced by this assumption. CONCLUSIONS: Since homogeneous between-study variance assumption is a strong assumption, it is crucial to test the validity of this assumption before conducting a network meta-analysis. Here we propose and validate a method for testing this single between-study variance assumption which is widely used for many NMA.

Adversarial Domain Adaptation With Prototype-Based Normalized Output Conditioner.

Domain adversarial training has become a prevailing and effective paradigm for unsupervised domain adaptation (UDA). To successfully align the multi-modal data structures across domains, the following works exploit discriminative information in the adversarial training process, e.g., using multiple class-wise discriminators and involving conditional information in the input or output of the domain discriminator. However, these methods either require non-trivial model designs or are inefficient for UDA tasks. In this work, we attempt to address this dilemma by devising simple and compact conditional domain adversarial training methods. We first revisit the simple concatenation conditioning strategy where features are concatenated with output predictions as the input of the discriminator. We find the concatenation strategy suffers from the weak conditioning strength. We further demonstrate that enlarging the norm of concatenated predictions can effectively energize the conditional domain alignment. Thus we improve concatenation conditioning by normalizing the output predictions to have the same norm of features, and term the derived method as Normalized OutpUt coNditioner (NOUN). However, conditioning on raw output predictions for domain alignment, NOUN suffers from inaccurate predictions of the target domain. To this end, we propose to condition the cross-domain feature alignment in the prototype space rather than in the output space. Combining the novel prototype-based conditioning with NOUN, we term the enhanced method as PROtotype-based Normalized OutpUt coNditioner (PRONOUN). Experiments on both object recognition and semantic segmentation show that NOUN can effectively align the multi-modal structures across domains and even outperform state-of-the-art domain adversarial training methods. Together with prototype-based conditioning, PRONOUN further improves the adaptation performance over NOUN on multiple object recognition benchmarks for UDA. Code is available at https://github.com/tim-learn/NOUN.

Mycoplasma hyopneumoniae Surveillance in Pig Populations: Establishing Sampling Guidelines for Detection in Growing Pigs.

Antemortem detection of Mycoplasma hyopneumoniae infection in swine production systems has relied on antibody testing, but the availability of tests based on DNA detection and novel diagnostic specimens, e.g., tracheal swabs and oral fluids, has the potential to improve M. hyopneumoniae surveillance. A field study was performed over a 14-week period during which 10 pigs in one pen at the center of a room with 1,250 6-week-old pigs housed in 46 pens were intratracheally inoculated with M. hyopneumoniae Thereafter, one tracheal sample, four serum samples, and one oral fluid sample were collected from every pen at 2-week intervals. Tracheal and oral fluid samples were tested for M. hyopneumoniae DNA and serum samples for M. hyopneumoniae antibody. Test results were modeled using a hierarchical Bayesian model, based on a latent spatial piecewise exponential survival model, to estimate the probability of detection by within-pen prevalence, number of positive pens in the barn, sample allocation, sample size, and sample type over time. Analysis showed that tracheal samples provided the earliest detection, especially at large sample sizes. While serum samples are more commonly collected and are less expensive to test, high probability of detection estimates were only obtained 30 days postexposure at large sample sizes. In all scenarios, probability of detection estimates for oral fluids within 30 days were significantly lower than those for tracheal and serum samples. Ultimately, the choice of specimen type, sample number, and assay will depend on testing objectives and economics, but the estimates provided here will assist in the design of M. hyopneumoniae surveillance and monitoring programs for different situations.

Active regional surveillance for early detection of exotic/emerging pathogens of swine: A comparison of statistical methods for farm selection.

In this study, five spatially balanced sampling methods, i.e., generalized random-tessellation stratified (GRTS), local pivotal method (LPM), spatially correlated Poisson sampling (SCPS), local cube method (LCUBE), and balanced acceptance sampling (BAS) were compared to simple random sampling (SRS) based on a livestock disease transmission model on a hypothetical region (195 km × 300 km) populated with 6000 farms in terms of the probability of detection by sample size. Given a fixed sample size, four of the five spatially balanced sampling methods provided better performance than SRS, i.e., higher probabilities of detecting at least one infected farms over a range of regional prevalence evaluated (1%-5%). That is, for any given probability of detection, spatially balanced methods required testing fewer farms than SRS. In an era of pandemics, active regional surveillance for early detection of emerging pathogens becomes urgent, yet shrinking budgets impose intractable constraints. The better performance and higher efficiency of spatially balanced sampling methods suggests a potential improvement in regional livestock disease surveillances and a partial solution to the challenge of affordable surveillance.

How to Conduct a Bayesian Network Meta-Analysis.

Network meta-analysis is a general approach to integrate the results of multiple studies in which multiple treatments are compared, often in a pairwise manner. In this tutorial, we illustrate the procedures for conducting a network meta-analysis for binary outcomes data in the Bayesian framework using example data. Our goal is to describe the workflow of such an analysis and to explain how to generate informative results such as ranking plots and treatment risk posterior distribution plots. The R code used to conduct a network meta-analysis in the Bayesian setting is provided at GitHub.

A method of back-calculating the log odds ratio and standard error of the log odds ratio from the reported group-level risk of disease.

In clinical trials and observational studies, the effect of an intervention or exposure can be reported as an absolute or relative comparative measure such as risk difference, odds ratio or risk ratio, or at the group level with the estimated risk of disease in each group. For meta-analysis of results with covariate adjustment, the log of the odds ratio (log odds ratio), with its standard error, is a commonly used measure of effect. However, extracting the adjusted log odds ratio from the reported estimates of disease risk in each group is not straightforward. Here, we propose a method to transform the adjusted probability of the event in each group to the log of the odds ratio and obtain the appropriate (approximate) standard error, which can then be used in a meta-analysis. We also use example data to compare our method with two other methods and show that our method is superior in calculating the standard error of the log odds ratio.

Efficacy of bacterial vaccines to prevent respiratory disease in swine: a systematic review and network meta-analysis.

A systematic review and network meta-analysis (MA) was conducted to address the question, 'What is the efficacy of bacterial vaccines to prevent respiratory disease in swine?' Four electronic databases and the grey literature were searched to identify clinical trials in healthy swine where at least one intervention arm was a commercially available vaccine for one or more bacterial pathogens associated with respiratory disease in swine, including Mycoplasma hyopneumoniae, Actinobacillus pleuropneumonia, Actinobacillus suis, Bordetella bronchiseptica, Pasteurella multocida, Stretococcus suis, Haemophils parasuis, and Mycoplasma hyorhinis. To be eligible, trials had to measure at least one of the following outcomes: incidence of clinical morbidity, mortality, lung lesions, or total antibiotic use. There were 179 eligible trials identified in 146 publications. Network MA was undertaken for morbidity, mortality, and the presence or absence of non-specific lung lesions. However, there was not a sufficient body of research evaluating the same interventions and outcomes to allow a meaningful synthesis of the comparative efficacy of the vaccines. To build this body of research, additional rigor in trial design and analysis, and detailed reporting of trial methods and results are warranted.

A systematic review of the efficacy of antibiotics for the prevention of swine respiratory disease.

Prevention and control of respiratory disease is a major contributor to antibiotic use in swine. A systematic review was conducted to address the question, 'What is the comparative efficacy of antimicrobials for the prevention of swine respiratory disease?' Eligible studies were controlled trials published in English evaluating prophylactic antibiotics in swine, where clinical morbidity, mortality, or total antibiotic use was assessed. Four databases and the gray literature were searched for relevant articles. Two reviewers working independently screened titles and abstracts for eligibility followed by full-text articles, and then extracted data and evaluated risk of bias for eligible trials. There were 44 eligible trials from 36 publications. Clinical morbidity was evaluated in eight trials where antibiotics were used in nursery pigs and 10 trials where antibiotics were used in grower pigs. Mortality was measured in 22 trials in nursery pigs and 12 trials in grower pigs. There was heterogeneity in the antibiotic interventions and comparisons published in the literature; thus, there was insufficient evidence to allow quantification of the efficacy, or relative efficacy, of antibiotic interventions. Concerns related to statistical non-independence and quality of reporting were noted in the included trials.

The efficacy of litter management strategies to prevent morbidity and mortality in broiler chickens: a systematic review and network meta-analysis.

A systematic review and network meta-analysis (NMA) were conducted to address the question, 'What is the efficacy of litter management strategies to reduce morbidity, mortality, condemnation at slaughter, or total antibiotic use in broilers?' Eligible studies were clinical trials published in English evaluating the efficacy of litter management in broilers on morbidity, condemnations at slaughter, mortality, or total antibiotic use. Multiple databases and two conference proceedings were searched for relevant literature. After relevance screening and data extraction, there were 50 trials evaluating litter type, 22 trials evaluating litter additives, 10 trials comparing fresh to re-used litter, and six trials evaluating floor type. NMAs were conducted for mortality (61 trials) and for the presence or absence of footpad lesions (15 trials). There were no differences in mortality among the litter types, floor types, or additives. For footpad lesions, peat moss appeared beneficial compared to straw, based on a small number of comparisons. In a pairwise meta-analysis, there was no association between fresh versus used litter on the risk of mortality, although there was considerable heterogeneity among studies (I2 = 66%). There was poor reporting of key design features in many studies, and analyses rarely accounted for non-independence of observations within flocks.

Frequency downconversion with independent multichannel phase shifting and zero-intermediate-frequency receiving based on optical frequency shift and polarization multiplexing.

Photonic microwave frequency downconversion with independent multichannel phase shifting and zero-intermediate-frequency (IF) receiving via an integrated polarization multiplexing dual-parallel Mach-Zehnder modulator (MZM) is proposed. Based on the ideas of optical frequency shift and polarization multiplexing, the radio frequency (RF) signal is frequency downconverted to multichannel IF signals with the phases independently and arbitrarily tuned by adjusting the polarization controllers or even frequency downconverted to baseband directly by choosing two quadrature channels. In the simulation, the gain of our proposed frequency downconversion system is higher than that of the conventional two cascaded MZMs' system, and the phase shift with the range of 360° can be obtained concurrently. Furthermore, 2.5 Gbit/s RF vector signals centered at 10 GHz with different modulation formats are successfully demodulated.

Structure improvements and numerical simulation of supersonic separators with diversion cone for separation and purification.

In the improved supersonic separator with the diversion cone, the reflow channel and the flush-type drain structure are adopted to overcome two shortcomings: the shock wave that easily appears in the diverging section of the nozzle and the swirling flow that occurs in subsonic conditions with poor efficiency, which makes the low-temperature section short and the cooling effect unsatisfactory. In this study, the distribution of the main parameters and the effects of the inlet temperature and outlet angle of the swirler were investigated by numerical simulation. The results indicated that the internal extension structure severely damaged the supersonic flow in the nozzle, while the flush type drainage port slightly influenced the fluid. The smaller outlet angle of the drainage port reduced its effect on the supersonic flow. Moreover, the improved device with the reflow enlarges the supersonic region and exhibits the better performance. In addition, it achieves a low temperature (221 K) and high centrifugal acceleration (2.2 × 107 m s-2). Moreover, the inlet temperature of 300-320 K and the outlet angle of 50°-60° are recommended for the improved supersonic separator based on the comprehensive consideration of good expansion characteristics and centrifugal separation performance.

[Posterior short-segment pedicle screw fixation combined with vertebroplasty for the treatment of thoracolumbar burst fractures].

OBJECTIVE: To evaluate the clinical efficacy of posterior short-segment pedicle screw fixation combined reduction of central end-plate by end-plate expand clamp and vertebroplasty with calcium phosphate cement for the treatment of thoracolumbar burst fractures. METHODS: Thirty patients with thoracolumbar burst fractures were treated with posterior pedicle screw fixation combined reduction of central end-plate by end-plate expand clamp and vertebroplasty with calcium phosphate cement. There were 22 males and 8 females with an average of 47 years (range from 25 to 71 years). Segment of fracture had 1 case in T11, 5 in T12, 14 in L1, 8 in L2, 2 in L3, 1 in L4, 1 in L5. According to Denis typing, 4 cases were type A, 25 type B, 1 type C, 1 type D, 1 type E. The relative anterior height of vertebral body and the vertebral angle were measured before and after operation and during the follow-up period (8 months after operation) through X-ray, the failure of internal fixation and recurrent kyphosis were evaluated during the follow-up period. Vertebral intracorporeal gap was measured by CT images after operation and the central end-plate fracture and reduction were observed by the reconstructed CT images (sagittal and coronary) before and after operation. RESULTS: All patients were followed up from 8 to 15 months with an average of 12 months. Relative anterior height of vertebral body and vertebral angle were well restored after operation, and there was no significant change between after operation and 8 months after operation. Preoperative,postoperative and 8 months after operation, relative anterior height of vertebral body respectively was 40.1%, 98.2%, 97.8%, vertebral angle respectively was 18.30, 2.70, 3.20. No failure of internal fixation and recurrent kyphosis were found during the follow-up period. The vertebral intracorporeal gap was about 3.1% and reduction of central endplate fracture was satisfactory. CONCLUSION: Posterior short-segment pedicle screw fixation combined with vertebroplasty with calcium phosphate cement can provide excellent reduction of post-traumatic segmental kyphosis and restore vertebral body height in the fracture level, prevent the failure of internal fixation which is an ideal method for the treatment of thoracolumbar burst fractures.