STALLION: a stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction.

Protein post-translational modification (PTM) is an important regulatory mechanism that plays a key role in both normal and disease states. Acetylation on lysine residues is one of the most potent PTMs owing to its critical role in cellular metabolism and regulatory processes. Identifying protein lysine acetylation (Kace) sites is a challenging task in bioinformatics. To date, several machine learning-based methods for the in silico identification of Kace sites have been developed. Of those, a few are prokaryotic species-specific. Despite their attractive advantages and performances, these methods have certain limitations. Therefore, this study proposes a novel predictor STALLION (STacking-based Predictor for ProkAryotic Lysine AcetyLatION), containing six prokaryotic species-specific models to identify Kace sites accurately. To extract crucial patterns around Kace sites, we employed 11 different encodings representing three different characteristics. Subsequently, a systematic and rigorous feature selection approach was employed to identify the optimal feature set independently for five tree-based ensemble algorithms and built their respective baseline model for each species. Finally, the predicted values from baseline models were utilized and trained with an appropriate classifier using the stacking strategy to develop STALLION. Comparative benchmarking experiments showed that STALLION significantly outperformed existing predictor on independent tests. To expedite direct accessibility to the STALLION models, a user-friendly online predictor was implemented, which is available at: http://thegleelab.org/STALLION.

Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2.

Coronavirus disease 2019 (COVID-19) has impacted public health as well as societal and economic well-being. In the last two decades, various prediction algorithms and tools have been developed for predicting antiviral peptides (AVPs). The current COVID-19 pandemic has underscored the need to develop more efficient and accurate machine learning (ML)-based prediction algorithms for the rapid identification of therapeutic peptides against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Several peptide-based ML approaches, including anti-coronavirus peptides (ACVPs), IL-6 inducing epitopes and other epitopes targeting SARS-CoV-2, have been implemented in COVID-19 therapeutics. Owing to the growing interest in the COVID-19 field, it is crucial to systematically compare the existing ML algorithms based on their performances. Accordingly, we comprehensively evaluated the state-of-the-art IL-6 and AVP predictors against coronaviruses in terms of core algorithms, feature encoding schemes, performance evaluation metrics and software usability. A comprehensive performance assessment was then conducted to evaluate the robustness and scalability of the existing predictors using well-constructed independent validation datasets. Additionally, we discussed the advantages and disadvantages of the existing methods, providing useful insights into the development of novel computational tools for characterizing and identifying epitopes or ACVPs. The insights gained from this review are anticipated to provide critical guidance to the scientific community in the rapid design and development of accurate and efficient next-generation in silico tools against SARS-CoV-2.

A benchmarking framework for the accurate and cost-effective detection of clinically-relevant structural variants for cancer target identification and diagnosis.

BACKGROUND: Accurate clinical structural variant (SV) calling is essential for cancer target identification and diagnosis but has been historically challenging due to the lack of ground truth for clinical specimens. Meanwhile, reduced clinical-testing cost is the key to the widespread clinical utility. METHODS: We analyzed massive data from tumor samples of 476 patients and developed a computational framework for accurate and cost-effective detection of clinically-relevant SVs. In addition, standard materials and classical experiments including immunohistochemistry and/or fluorescence in situ hybridization were used to validate the developed computational framework. RESULTS: We systematically evaluated the common algorithms for SV detection and established an expert-reviewed SV call set of 1,303 tumor-specific SVs with high-evidence levels. Moreover, we developed a random-forest-based decision model to improve the true positive of SVs. To independently validate the tailored 'two-step' strategy, we utilized standard materials and classical experiments. The accuracy of the model was over 90% (92-99.78%) for all types of data. CONCLUSION: Our study provides a valuable resource and an actionable guide to improve cancer-specific SV detection accuracy and clinical applicability.

Spotlights on the trends in performance assessment of qualitative in vitro diagnostic medical devices in transfusion medicine.

For reliable clinical decisions in transfusion medicine, assessing the performance of qualitative tests performed in medical laboratories is critical. When false results are reported, these can lead to an adverse reaction to blood components. Good performance assessment practices are essential for this kind of scenario, and they still remain as one of the many unmet high-priority challenges in this area. This paper aims to provide an overview of the current trends in this field. A review of the IFCC-IUPC. qualitative vocabulary was carried out, and a particular focus was given to the evaluation protocols CLSI EP12-A3 and Eurachem AQA, such as the European Union Regulation for class D in vitro diagnostic medical devices. There is a consistency between the current protocols and recognized performance assessment principles, which are mandatory in transfusion service labs. We believe that a revised imprecision interval approach and models based on emerging qualitative test types may prove beneficial in the long run. It is also important to emphasize the uncertainty of proportions to mitigate the risk of misclassification.

Conducting an objective structured clinical examination under COVID-restricted conditions.

BACKGROUND: The administration of performance assessments during the coronavirus disease of 2019 (COVID-19) pandemic posed many challenges, especially for examinations employed as part of certification and licensure. The National Assessment Collaboration (NAC) Examination, an Objective Structured Clinical Examination (OSCE), was modified during the pandemic. The purpose of this study was to gather evidence to support the reliability and validity of the modified NAC Examination. METHODS: The modified NAC Examination was delivered to 2,433 candidates in 2020 and 2021. Cronbach's alpha, decision consistency, and accuracy values were calculated. Validity evidence includes comparisons of scores and sub-scores for demographic groups: gender (male vs. female), type of International Medical Graduate (IMG) (Canadians Studying Abroad (CSA) vs. non-CSA), postgraduate training (PGT) (no PGT vs. PGT), and language of examination (English vs. French). Criterion relationships were summarized using correlations within and between the NAC Examination and the Medical Council of Canada Qualifying Examination (MCCQE) Part I scores. RESULTS: Reliability estimates were consistent with other OSCEs similar in length and previous NAC Examination administrations. Both total score and sub-score differences for gender were statistically significant. Total score differences by type of IMG and PGT were not statistically significant, but sub-score differences were statistically significant. Administration language was not statistically significant for either the total scores or sub-scores. Correlations were all statistically significant with some relationships being small or moderate (0.20 to 0.40) or large (> 0.40). CONCLUSIONS: The NAC Examination yields reliable total scores and pass/fail decisions. Expected differences in total scores and sub-scores for defined groups were consistent with previous literature, and internal relationships amongst NAC Examination sub-scores and their external relationships with the MCCQE Part I supported both discriminant and criterion-related validity arguments. Modifications to OSCEs to address health restrictions can be implemented without compromising the overall quality of the assessment. This study outlines some of the validity and reliability analyses for OSCEs that required modifications due to COVID.

Reliability and Validity of the Strain Gauge "GSTRENGTH" for Measuring Peak Force in the Isometric Belt Squat at Different Joint Angles.

Since isometric training is gaining popularity, some devices are being developed to test isometric force as an alternative to the more expensive force plates (FPs); thus, the aim of this study was to test the reliability and validity of "GSTRENGTH" for measuring PF in the isometric belt squat exercise. Five subjects performed 24 contractions at three different knee angles (90°, 105° and 120°) on two occasions (120 total cases). Peak force data were measured using FPs and a strain gauge (SG) and analyzed by Pearson's product-moment correlation coefficient, ICCs, Cronbach's alpha, a paired sample t-test and Bland-Altman plots. Perfect or almost perfect relationships (r: 0.999-1) were found with an almost perfect or perfect level of agreement (ICCs: 0.992-1; α: 0.998-1). The t-test showed significant differences for the raw data but not for the predictions by the equations obtained with the SG values. The Bland-Altman plots, when significant, showed trivial to moderate values for systematic bias in general. In conclusion, "GSTRENGTH" was shown to be a valid alternative to FPs for measuring PF.

On the Performance of a Horizontally Mounted ADCP in an Energetic Tidal Environment for Floating Tidal Turbine Applications.

Incident flow measurement is key in the tidal industry for conducting power performance assessments. This paper explores the use of a horizontally mounted Nortek Signature 500 Acoustic Doppler Current Profiler (ADCP) as a means for incident flow measurement onboard a utility-scale tidal turbine. This study shows that the measurement range of an ADCP mounted horizontally in highly dynamic tidal flow (up to 4 m/s) is less than the maximum range stated by the manufacturer. The ability for the horizontal ADCP to accurately resolve velocities in a multi-beam configuration is also analysed. Effects from both vertical shear and beam selection result in incident flow velocities that differ from a single horizontal beam recording. The maximum measurement range of the instrument is found to depend on current speed and on the proportion of data loss that is acceptable to the user. The ability of the ADCP to record data from the free-stream velocity two equivalent diameters upstream of the O2, as set out by IEC TS 62600-200, is considered. It is found that at this distance, there is 90% data loss. Accepting only 10% data loss across all flow speeds resulted in a maximum range of 31 m for a Nortek Signature 500 in this study. While some limitations of an ADCP deployed horizontally in highly energetic tidal flow are identified, the benefits of mounting the sensor close to the rotor facing horizontally into the incoming flow mean that valuable data are still produced for tidal turbine operators.

Gender Differences in Core Muscle Morphology of Elite Alpine Skiers: Insights from Ultrasonography.

This study investigates gender differences in core muscle morphology among elite alpine skiers using ultrasonography, highlighting significant disparities that could influence training and injury prevention strategies. METHODS: A cross-sectional design was employed, examining ultrasound imaging (USI) in 22 elite skiers (11 male, 11 female) to assess the thickness of the external oblique (EO), internal oblique (IO), transversus abdominis (TrAb), and rectus abdominis (RA) muscles. RESULTS: Significant differences were noted, with male skiers displaying greater muscle thickness, particularly in the right IO and RA and left IO, EO, TrAb, and RA. CONCLUSIONS: These findings suggest that male and female skiers may require different training approaches to optimize performance and reduce injury risks. This research contributes to a deeper understanding of the physical demands on elite skiers and underscores the need for gender-specific training regimens to enhance athletic outcomes and prevent injuries.

Performance Assessment for the Validation of Wireless Communication Engines in an Innovative Wearable Monitoring Platform.

In today's health-monitoring applications, there is a growing demand for wireless and wearable acquisition platforms capable of simultaneously gathering multiple bio-signals from multiple body areas. These systems require well-structured software architectures, both to keep different wireless sensing nodes synchronized each other and to flush collected data towards an external gateway. This paper presents a quantitative analysis aimed at validating both the wireless synchronization task (implemented with a custom protocol) and the data transmission task (implemented with the BLE protocol) in a prototype wearable monitoring platform. We evaluated seven frequencies for exchanging synchronization packets (10 Hz, 20 Hz, 30 Hz, 40 Hz, 50 Hz, 60 Hz, 70 Hz) as well as two different BLE configurations (with and without the implementation of a dynamic adaptation of the BLE Connection Interval parameter). Additionally, we tested BLE data transmission performance in five different use case scenarios. As a result, we achieved the optimal performance in the synchronization task (1.18 ticks as median synchronization delay with a Min-Max range of 1.60 ticks and an Interquartile range (IQR) of 0.42 ticks) when exploiting a synchronization frequency of 40 Hz and the dynamic adaptation of the Connection Interval. Moreover, BLE data transmission proved to be significantly more efficient with shorter distances between the communicating nodes, growing worse by 30.5% beyond 8 m. In summary, this study suggests the best-performing network configurations to enhance the synchronization task of the prototype platform under analysis, as well as quantitative details on the best placement of data collectors.

Climate change impact and adaptation assessment for road drainage systems.

Climate change exhibits a clear trend of escalating frequency and intensity of extreme weather events, posing heightened risks to drainage systems along the existing road networks. However, very few studies to date have investigated the consequences of projected future changes in rainfall on main road drainage and the resulting risk of road flooding. The work presented in this paper builds on the limited research by introducing a probabilistic model for assessing the impact of climate change on road drainage systems, incorporating climate uncertainty and drainage system variation. The probabilistic scenario-based model and associated framework offer a practical and innovative method for estimating the impact of short-duration storms under future climates for 2071-2100, in the absence of fine-resolution spatio-temporal data. The model also facilitates the assessment of the effectiveness of a climate adaptation strategy. An illustrative case-study of a road drainage system located in the south of Ireland is presented. It was found that the probability of road flooding during intense rainfall is projected to surpass the current acceptable limits set by Irish standards. Assessment of a proactive climate adaptation strategy implemented in 2015 indicated it may need to be adjusted to further reduce climate change impacts and optimise adaptation costs.

Provision of oral healthcare services in WHO-EMR countries: a scoping review.

Global neglect of oral healthcare services (OHCS) provision, mainly in Low- and Middle-Income Countries, exacerbates the deterioration of health systems and increases global health inequality.ObjectivesThe objective is to explore the profiles of available oral healthcare services in the WHO Eastern Mediterranean Region (EMR) countries.MethodsA systematic literature search was conducted of grey literature and databases (PubMed, Medline, Embase, and the Cochrane Library). Peer-reviewed articles that reviewed and/or evaluated OHCS in WHO-EMR countries were identified. No time or language limitations were applied. Two independent reviewers conducted the screening and data extraction. A third reviewer arbitrated disagreement. The evaluation of the OHCS provision followed the WHO framework for health system performance assessment. The extraction included socio-demographic characteristics of the studied population, OHCS profile, responsiveness, and health insurance coverage.ResultsOne hundred and thirty-seven studies were identified. The studies that met the inclusion criteria were fifteen published between 1987 and 2016. In addition, two reports were published in 2022. The included studies were conducted in Pakistan, Saudi Arabia, Iran, Libya, Egypt, Oman, Syria, Jourdan, Kuwait, and Tunisia. Generally, Ministries of Health are the main providers of OHCS. The provision for national dental care prevention programmes was highly limited. Furthermore, most of these Ministries of Health have struggled to meet their local populations' dental needs due to limited finances and resources for OHCS.ConclusionsOral and dental diseases are highly prevalent in the WHO-EMR region and the governments of the region face many challenges to meeting the OHCS needs of the population. Therefore, further studies to assess and re-design the OHCS in these countries to adapt dental care prevention into national health programmes are crucial.

Large-scale comparative review and assessment of computational methods for anti-cancer peptide identification.

Anti-cancer peptides (ACPs) are known as potential therapeutics for cancer. Due to their unique ability to target cancer cells without affecting healthy cells directly, they have been extensively studied. Many peptide-based drugs are currently evaluated in the preclinical and clinical trials. Accurate identification of ACPs has received considerable attention in recent years; as such, a number of machine learning-based methods for in silico identification of ACPs have been developed. These methods promote the research on the mechanism of ACPs therapeutics against cancer to some extent. There is a vast difference in these methods in terms of their training/testing datasets, machine learning algorithms, feature encoding schemes, feature selection methods and evaluation strategies used. Therefore, it is desirable to summarize the advantages and disadvantages of the existing methods, provide useful insights and suggestions for the development and improvement of novel computational tools to characterize and identify ACPs. With this in mind, we firstly comprehensively investigate 16 state-of-the-art predictors for ACPs in terms of their core algorithms, feature encoding schemes, performance evaluation metrics and webserver/software usability. Then, comprehensive performance assessment is conducted to evaluate the robustness and scalability of the existing predictors using a well-prepared benchmark dataset. We provide potential strategies for the model performance improvement. Moreover, we propose a novel ensemble learning framework, termed ACPredStackL, for the accurate identification of ACPs. ACPredStackL is developed based on the stacking ensemble strategy combined with SVM, Naïve Bayesian, lightGBM and KNN. Empirical benchmarking experiments against the state-of-the-art methods demonstrate that ACPredStackL achieves a comparative performance for predicting ACPs. The webserver and source code of ACPredStackL is freely available at http://bigdata.biocie.cn/ACPredStackL/ and https://github.com/liangxiaoq/ACPredStackL, respectively.

Crowd-sourced and expert video assessment in minimally invasive esophagectomy.

BACKGROUND: Video-based assessment by experts may structurally measure surgical performance using procedure-specific competency assessment tools (CATs). A CAT for minimally invasive esophagectomy (MIE-CAT) was developed and validated previously. However, surgeon's time is scarce and video assessment is time-consuming and labor intensive. This study investigated non-procedure-specific assessment of MIE video clips by MIE experts and crowdsourcing, collective surgical performance evaluation by anonymous and untrained laypeople, to assist procedure-specific expert review. METHODS: Two surgical performance scoring frameworks were used to assess eight MIE videos. First, global performance was assessed with the non-procedure-specific Global Operative Assessment of Laparoscopic Skills (GOALS) of 64 procedural phase-based video clips < 10 min. Each clip was assessed by two MIE experts and > 30 crowd workers. Second, the same experts assessed procedure-specific performance with the MIE-CAT of the corresponding full-length video. Reliability and convergent validity of GOALS for MIE were investigated using hypothesis testing with correlations (experience, blood loss, operative time, and MIE-CAT). RESULTS: Less than 75% of hypothesized correlations between GOALS scores and experience of the surgical team (r < 0.3), blood loss (r = - 0.82 to 0.02), operative time (r = - 0.42 to 0.07), and the MIE-CAT scores (r = - 0.04 to 0.76) were met for both crowd workers and experts. Interestingly, experts' GOALS and MIE-CAT scores correlated strongly (r = 0.40 to 0.79), while crowd workers' GOALS and experts' MIE-CAT scores correlations were weak (r = - 0.04 to 0.49). Expert and crowd worker GOALS scores correlated poorly (ICC ≤ 0.42). CONCLUSION: GOALS assessments by crowd workers lacked convergent validity and showed poor reliability. It is likely that MIE is technically too difficult to assess for laypeople. Convergent validity of GOALS assessments by experts could also not be established. GOALS might not be comprehensive enough to assess detailed MIE performance. However, expert's GOALS and MIE-CAT scores strongly correlated indicating video clip (instead of full-length video) assessments could be useful to shorten assessment time.

Universal meta-competencies of operative performances: a literature review and qualitative synthesis.

BACKGROUND: Prioritizing patient health is essential, and given the risk of mortality, surgical techniques should be objectively evaluated. However, there is no comprehensive cross-disciplinary system that evaluates skills across all aspects among surgeons of varying levels. Therefore, this study aimed to uncover universal surgical competencies by decomposing and reconstructing specific descriptions in operative performance assessment tools, as the basis of building automated evaluation system using computer vision and machine learning-based analysis. METHODS: The study participants were primarily expert surgeons in the gastrointestinal surgery field and the methodology comprised data collection, thematic analysis, and validation. For the data collection, participants identified global operative performance assessment tools according to detailed inclusion and exclusion criteria. Thereafter, thematic analysis was used to conduct detailed analyses of the descriptions in the tools where specific rules were coded, integrated, and discussed to obtain high-level concepts, namely, "Skill meta-competencies." "Skill meta-competencies" was recategorized for data validation and reliability assurance. Nine assessment tools were selected based on participant criteria. RESULTS: In total, 189 types of skill performances were extracted from the nine tool descriptions and organized into the following five competencies: (1) Tissue handling, (2) Psychomotor skill, (3) Efficiency, (4) Dissection quality, and (5) Exposure quality. The evolutionary importance of these competences' different evaluation targets and purpose over time were assessed; the results showed relatively high reliability, indicating that the categorization was reproducible. The inclusion of basic (tissue handling, psychomotor skill, and efficiency) and advanced (dissection quality and exposure quality) skills in these competencies enhanced the tools' comprehensiveness. CONCLUSIONS: The competencies identified to help surgeons formalize and implement tacit knowledge of operative performance are highly reproducible. These results can be used to form the basis of an automated skill evaluation system and help surgeons improve the provision of care and training, consequently, improving patient prognosis.

Assessing the impact of COVID-19 on the performance of organ transplant services using data envelopment analysis.

Organ transplant is one of the best options for many medical conditions, and in many cases, it may be the only treatment option. Recent evidence suggests, however, that the COVID-19 pandemic might have detrimentally affected the provision of this type of healthcare services. The main purpose of this article is to use Data Envelopment Analysis and the Malmquist Index to assess the impact that the pandemic caused by the novel coronavirus SARS-CoV-2 had on the provision of solid organ transplant services. To this purpose, we use three complementary models, each focusing on specific aspects of the organ donation and transplantation process, and data from Brazil, which has one of the most extensive public organ transplant programs in the world. Using data from 17 States plus the Federal District, the results of our analysis show a significant drop in the performance of the services in terms of the organ donation and transplantation process from 2018 to 2020, but the results also indicate that not all aspects of the process and States were equally affected. Furthermore, by using different models, this research also allows us to gain a more comprehensive and informative assessment of the performance of the States in delivering this type of service and identify opportunities for reciprocal learning, expanding our knowledge on this important issue and offering opportunities for further research.

How progress evaluations are used in postgraduate education with longitudinal supervisor-trainee relationships: a mixed method study.

The combination of measuring performance and giving feedback creates tension between formative and summative purposes of progress evaluations and can be challenging for supervisors. There are conflicting perspectives and evidence on the effects supervisor-trainee relationships have on assessing performance. The aim of this study was to learn how progress evaluations are used in postgraduate education with longitudinal supervisor-trainee relationships. Progress evaluations in a two-year community-pharmacy specialization program were studied with a mixed-method approach. An adapted version of the Canadian Medical Education Directives for Specialists (CanMEDS) framework was used. Validity of the performance evaluation scores of 342 trainees was analyzed using repeated measures ANOVA. Semi-structured interviews were held with fifteen supervisors to investigate their response processes, the utility of the progress evaluations, and the influence of supervisor-trainee relationships. Time and CanMEDS roles affected the three-monthly progress evaluation scores. Interviews revealed that supervisors varied in their response processes. They were more committed to stimulating development than to scoring actual performance. Progress evaluations were utilized to discuss and give feedback on trainee development and to add structure to the learning process. A positive supervisor-trainee relationship was seen as the foundation for feedback and supervisors preferred the roles of educator, mentor, and coach over the role of assessor. We found that progress evaluations are a good method for directing feedback in longitudinal supervisor-trainee relationships. The reliability of scoring performance was low. We recommend progress evaluations to be independent of formal assessments in order to minimize roles-conflicts of supervisors.

Stroke pathway performance assessment: a retrospective observational study.

BACKGROUND AND AIM: Performance assessment of the Stroke Pathway is a key element in healthcare quality. The aim of this study has been to carry out a retrospective assessment of the Stroke Pathway in a first level Stroke Unit in Italy, analyzing the temporal trend of the Stroke Pathway performance and the impact of the COVID-19 pandemic. METHODS: A retrospective observational study was carried out analyzing data from 1/01/2010 to 31/12/2020. The following parameters were considered: volume and characteristics of patients with ischemic stroke undergoing intravenous thrombolysis, baseline modified Rankin Scale (mRS) and National Institutes of Health Stroke Scale (NIHSS) scores, Onset-to-Door (OTD), Door-To-Imaging (DTI) and Door-To-Needle (DTN) Times, mRS score 3 months after the ischemic event onset (3 m-mRS) and NIHSS score 24 h after the ischemic event onset (24 h-NIHSS). The study also compared the pre-COVID-19 pandemic period (March-December 2019) with the one immediately following it (March-December 2020). RESULTS: 418 patients were included. Over time, treatment was extended to older patients (mean age from 66.3 to 75.51 years; p = 0.006) and with a higher level of baseline disability (baseline mRS score from 0.22 to 1.22; p = 0.000). A statistically significant reduction over the years was found for DTN, going from 90 min to 61 min (p = 0.000) with also an increase in the number of thrombolysis performed within the "golden hour" - more than 50% in 2019 and more of 60% in 2020. Comparing pre- and during COVID-19 pandemic periods, the number of patients remained almost unchanged, but with a significantly higher baseline disability (mRS = 1.18 vs. 0.72, p = 0.048). The pre-hospital process indicator OTD increased from 88.13 to 118.48 min, although without a statistically significant difference (p = 0.197). Despite the difficulties for hospitals due to pandemic, the hospital process indicators DTI and DTN remained substantially unchanged, as well as the clinical outcome indicators 3 m-mRS, NHISS and 24 h-NHISS. CONCLUSIONS: The results of the retrospective assessment of the Stroke Pathway highlighted its positive impact both on hospital processes and patients' outcomes, even during the COVID-19 pandemic, so that the current performance is aligning itself with international goals. Moreover, the analysis showed the need of improvement actions for both hospital and pre-hospital phases. The Stroke Pathway should be improved with the thrombolysis starting in the diagnostic imaging department in order to further reduce the DTN score. Moreover, health education initiatives involving all the stakeholders should be promoted, also by using social media, to increase population awareness on timely recognition of stroke signs and symptoms and emergence medical services usage.

Validation of a Molecular Diagnostic Test for Circulating Tumor DNA by Next-Gen Sequencing.

A modified version of the PGDx elioTM Plasma Resolve assay was validated as a laboratory-developed test (LDT) for clinical use in the Molecular Diagnostics Laboratory at Fox Chase Cancer Center. The test detects single nucleotide variants (SNVs) and small insertions and deletions (indels) in 33 target genes using fragmented genomic DNA extracted from plasma. The analytical performance of this assay was assessed with reference standard DNA and 29 samples from cancer patients and detected 66 SNVs and 23 indels. Using 50 ng of input DNA, the sensitivity was 95.5% to detect SNVs at 0.5% allele frequency, and the specificity was 92.3%. The sensitivity to detect indels at 1% allele frequency was 70.4%. A cutoff of 0.25% variant allele frequency (VAF) was set up for diagnostic reporting. An inter-laboratory study of concordance with an orthologous test resulted in a positive percent agreement (PPA) of 91.7%.

Public commentary on teacher quality: an analysis of media comment on the teaching performance assessment.

In Australia, the Teaching Performance Assessment (TPA) is a relatively new, mandatory hurdle which must be completed just prior to the graduation stage of initial teacher education (ITE) programmes. This high-stakes task is one of a growing number of requirements to come out of the standards and accountability regime as outlined in the Australian Institute for Teaching and School Leadership (AITSL) document for accreditation for ITE programmes. We delve into the public commentary about the broader commission of preservice and graduate teacher quality in general and the TPA in particular. We draw on Bernstein's pedagogic identities and deductively apply this theory to explore this phenomenon. We use a data set of publicly available legacy media and social media tweets made over a ten-month period from August 2019 to May 2020 to reveal the focus, inherent bias and pedagogic identities promoted by these public discourses. The paper concludes with discussion about the implications of these drivers on the public perception of quality in ITE and on the status of teaching more broadly.

ANPELA: analysis and performance assessment of the label-free quantification workflow for metaproteomic studies.

Label-free quantification (LFQ) with a specific and sequentially integrated workflow of acquisition technique, quantification tool and processing method has emerged as the popular technique employed in metaproteomic research to provide a comprehensive landscape of the adaptive response of microbes to external stimuli and their interactions with other organisms or host cells. The performance of a specific LFQ workflow is highly dependent on the studied data. Hence, it is essential to discover the most appropriate one for a specific data set. However, it is challenging to perform such discovery due to the large number of possible workflows and the multifaceted nature of the evaluation criteria. Herein, a web server ANPELA (https://idrblab.org/anpela/) was developed and validated as the first tool enabling performance assessment of whole LFQ workflow (collective assessment by five well-established criteria with distinct underlying theories), and it enabled the identification of the optimal LFQ workflow(s) by a comprehensive performance ranking. ANPELA not only automatically detects the diverse formats of data generated by all quantification tools but also provides the most complete set of processing methods among the available web servers and stand-alone tools. Systematic validation using metaproteomic benchmarks revealed ANPELA's capabilities in 1 discovering well-performing workflow(s), (2) enabling assessment from multiple perspectives and (3) validating LFQ accuracy using spiked proteins. ANPELA has a unique ability to evaluate the performance of whole LFQ workflow and enables the discovery of the optimal LFQs by the comprehensive performance ranking of all 560 workflows. Therefore, it has great potential for applications in metaproteomic and other studies requiring LFQ techniques, as many features are shared among proteomic studies.