Pairwise Tests Research Articles

Preliminary study: Evaluating the reliability of cone-beam computed tomography images for upper airway volume in orthodontics

Objectives: The primary aim of this study was to evaluate the reliability of cone-beam computed tomography (CBCT) in measuring upper airway volume in orthodontics. The secondary aim was to compare the upper airway volumes between laypeople and military personnel (physically fit individuals). Material and Methods: This study included 36 male participants aged 21–29 years who had no upper airway pathology or history of upper airway surgery. CBCT scans had been previously obtained as part of routine dental checkups using a standardized protocol by the same operator. The digital imaging and communications in the medicine files of the subjects were imported into the 3D analysis software SimPlant® 17 Pro (Materialize Dental, Leuven, Belgium) to facilitate the measurement of upper airway volume. The upper airway volume was divided into three sections and measured on days 0 and 14 by the same operator. The intrarater intra-class correlation coefficient (ICC) and Bland-Altman plot were used to assess reliability. The upper airway volumes of the laypeople and military personnel were compared using Tukey’s pairwise test. Results: The variables demonstrated excellent reliability across all sections of the upper airway; the Superior part of the upper airway has an ICC of 0.993, the middle part of the upper airway has an ICC of 0.995, and the inferior part of the upper airway has an ICC of 0.989. The ICC for the entire upper airway was 0.987. The intrarater plot for superior airway measurement showed that 8 out of 8 measurements (100%) fell within the limits of agreement. Similarly, the intrarater plot for the middle airway measurements indicated that 8 out of 8 measurements (100%) fell within the limits of agreement. For inferior airway measurement, the intrarater plot revealed that 7 out of 8 measurements (87.5%) fell within the limits of agreement. No significant differences were found between the upper airway volumes of the laypeople and military personnel. Conclusion: Preliminary evidence suggests that CBCT using a standardized protocol is reliable for measuring upper airway volume. Separating the upper airway into three different parts also demonstrated high reliability and reproducibility among the raters. The ability to accurately measure the upper airway enhances the evaluation of the effects of orthodontic treatment by comparing the pre-and post-upper airway volume.

Pilot Study on the Relationship Between Different Lower Limb Raising Velocities and Trunk Muscle Contraction in Active Straight Leg Raise

Background/Objectives: The active straight leg raise requires intricate coordination between the hip, knee, pelvis, and spine. Despite its complexity, limited research has explored the relationship between lower limb raising velocity and trunk muscle motor control during an active straight leg raise in healthy individuals. This study aimed to explore the potential effects of increased lower limb raising velocity on core muscle contractions during active straight leg raises. Methods: Six healthy adult men (mean age: 24.5 ± 2.5 years) participated in this study. Electromyography signals were recorded using surface electrodes placed on the rectus abdominis, external oblique, and internal oblique/transverse abdominis muscles. The participants performed active straight leg raises at three different velocities: 3 s, 2 s, and as fast as possible (max). The electromyography data were analyzed from 250 ms before to 1000 ms after movement initiation, with muscle activity expressed as a percentage of the maximal voluntary isometric contraction. Statistical analyses were conducted using non-parametric tests, including the Friedman test for overall differences, followed by pairwise Wilcoxon signed-rank tests with Bonferroni correction for multiple comparisons (p < 0.05). Results: During the 250 ms before movement initiation, the internal oblique/transverse abdominis, external oblique, and rectus abdominis muscles showed greater activity in the max condition compared to the 3 s and 2 s conditions (Friedman test, p < 0.05), but no significant differences were found in pairwise comparisons (Wilcoxon test, p > 0.05). Similarly, during the 500 ms after movement initiation, internal oblique/transverse abdominis activity was higher in the max condition, with no significant pairwise differences observed. Conclusions: Faster lower limb raising velocities during active straight leg raise may enhance core stability by activating anticipatory and sustained internal oblique/transverse abdominis, external oblique, and rectus abdominis activity on the raised limb side. Training to promote this activation could improve dynamic stability in rapid or asymmetric movements.

An Assessment of Statistical Power for Analysis of Variance with Missing Data using Multiple Imputation

This study proposes a framework for statistical power assessment in the analysis of variance (ANOVA) models with missing data handled through multiple imputation. While existing literature has examined the power for t-tests with missing data, extending these techniques to ANOVA designs with multiple group means remains an open challenge. The methodology involves incorporating the variance component into an existing power model derived for a pairwise test, enabling explicit power estimation for two-factor, three-factor, and split-plot ANOVA designs with incomplete data. Empirical evaluations across varying effect sizes, missing data rates (8%, 16%, 40%), and numbers of imputations (20, 30, 40, 100) were conducted for both monotone and arbitrary patterns of missing data. The findings reveal that while power remains high at low missing data rates, it declines substantially with increasing missingness, particularly for higher proportions of missing data. Furthermore, arbitrary patterns of missing data exhibit slightly lower power compared to monotone patterns. The number of required imputations to achieve desired power levels depends on the missing data rate, with more imputations needed for higher proportions of missing data. This study provides a framework for power analysis in ANOVA models with missing data, addressing the critical need for reliable guidance in designing studies with incomplete data

Does trade uncertainty in US and China influence Indian banking stability: An analysis through the lens of banking regulation and compliance

Purpose A recent literature has documented the real effect of Trade Policy Uncertainty (TPU) on trade, stock markets and unemployment; however, there is no specific study that has examined how trade uncertainty influences banking sector stability. In this quest, this study aims to bridge this gap by examining the impact of TPU in the USA and China on the stability of the Indian banking sector. Additionally, the study aims to assess the moderating influence of banking regulation and supervision on the aforementioned relationship. Design/methodology/approach To quantify the above objectives, the study uses a robust set of econometric estimates, i.e. system generalised method of moments (Sys-GMM), fixed effect model and pair-wise Granger causality test on the alternative proxies of banking stability from 2000 to 2023. Findings The empirical estimates validate that TPU has a negative impact on the Indian banking stability. Moreover, the impact of the USA. TPU is much more significant on the Indian banking sector’s stability in comparison to the Chinese TPU. The empirical model further suggests that banking regulation and supervision moderate the negative influence of trade uncertainties on the Indian banking sector’s stability and assist in improving it. Finally, the pairwise causality test confirms a unidirectional causal relationship between the TPU in the USA and China and the stability of the Indian banking sector, thereby validating the transmission effect of trade uncertainty on this sector. Originality/value To the best of the author’s study, this study is original and offers useful policy recommendations for understanding the implications of trade uncertainty for banking stability. The study also offers insight to comprehend the role of banking regulation and compliance in mitigating the adverse repercussion of trade uncertainties on the banking sector’s stability.

Effects of concave thoracoplasty on chest circumference and ventilatory function in adolescence with idiopathic scoliosis

IntroductionAdolescent idiopathic scoliosis (AIS) can reduce rib cage volume, which mechanically overloads the respiratory musculature. A current study examines the influences of concave thoracoplasty on pulmonary function and chest circumference.MethodsThis study included thirty AIS patients of both genders, aged 12 to 18 years, who had a concave thoracoplasty with posterior correction. Pulmonary function, Cobb angles, and chest circumferences were measured before surgery, on the fifth day following surgery, and at three months.ResultsA paired t-test was used to compare Cobb angles and chest expansion before and after intervention in the AIS-studied group. The statistical analysis stated that there was a significant decrease in Cobb angles and chest expansion (<i>p</i> < 0.05) at post-intervention follow-ups compared to pre-intervention measurements with a change percentage of 56.13% and 18.90%, respectively. Bonferroni correction test was employed to evaluate a pairwise intervention for outcome variables that revealed there were insignificantly increases in vital capacity (VC), forced vital capacity (FVC), and maximal voluntary breathing (MVV) after the intervention compared to before intervention (<i>p</i> > 0.05). In contrast, the pairwise comparison test between pre-intervention versus follow-up revealed time effect had significantly increased VC, FVC, and MVV at post-intervention compared to 3 months after the intervention with improvement percentages of 16.51%, 16.11%, and 22.16%, respectively.ConclusionsPatients with AIS who underwent concave thoracoplasty showed greater improvements in Cobb angles and pulmonary function tests 3 months after surgical intervention. Future research activities should emphasize elucidating areas of confusion to improve care in the AIS.

Evaluating the Performance of the Carrot Slicer Machine

The study was carried out to evaluate the performance of the carrot slicer machine. An experiment was conducted with a multi-factor factorial design under a randomized complete block design. Using the Statistix 8 software, the experiments' collected data were statistically examined. The analysis of variance indicated that the effects of machine speed and feed rate on throughput capacity, efficiency, and percentage loss of the machine were significant at the 5% probability level. The results of the least significance difference pairwise comparison tests revealed that the treatment combination means did not differ significantly from one another at the 5% level. The key physical properties of the carrot including moisture content, angle of repose, bulk density, porosity, coefficient of friction, geometric mean diameter, arithmetic mean diameter, equivalent mean diameter, sphericity, surface area and aspect ratio were obtained as 84.3%, 39.4°, 469.5 kg m-3, 59.8%, 0.78, 47.8 mm, 62.18 mm, 83.7 mm, 0.55, 57.67 cm2, and 0.27, correspondingly. The results showed that the maximum throughput capacity of 621.4 kg h-1 was recorded at 550 rpm machine speed while the minimum throughput capacity of 511.6 kg h-1 was recorded at 350 rpm machine speed. It has been found that the maximum machine efficiency was 96.03% at 550 rpm machine speed whereas the minimum machine efficiency was 92.5% at 350 rpm machine speed. The investigation results revealed that the minimum percentage loss was 4.2% at 550 rpm machine speed whereas the maximum percentage loss was 7.8% at 350 rpm machine speed. The test results suggested that the carrot slicer machine was found to be very effective for processing the vegetable root crop of carrots for end users.

Combining crystallographic and binding affinity data towards a novel dataset of small molecule overlays

Although small molecule superposition is a standard technique in drug discovery, a rigorous performance assessment of the corresponding methods is currently challenging. Datasets in this field are sparse, small, tailored to specific applications, unavailable, or outdated. The newly developed LOBSTER set described herein offers a publicly available and method-independent dataset for benchmarking and method optimization. LOBSTER stands for “Ligand Overlays from Binding SiTe Ensemble Representatives”. All ligands were derived from the PDB in a fully automated workflow, including a ligand efficiency filter. So-called ligand ensembles were assembled by aligning identical binding sites. Thus, the ligands within the ensembles are superimposed according to their experimentally determined binding orientation and conformation. Overall, 671 representative ligand ensembles comprise 3583 ligands from 3521 proteins. Altogether, 72,734 ligand pairs based on the ensembles were grouped into ten distinct subsets based on their volume overlap, for the benefit of introducing different degrees of difficulty for evaluating superposition methods. Statistics on the physicochemical properties of the compounds indicate that the dataset represents drug-like compounds. Consensus Diversity Plots show predominantly high Bemis–Murcko scaffold diversity and low median MACCS fingerprint similarity for each ensemble. An analysis of the underlying protein classes further demonstrates the heterogeneity within our dataset. The LOBSTER set offers a variety of applications like benchmarking multiple as well as pairwise alignments, generating training and test sets, for example based on time splits, or empirical software performance evaluation studies. The LOBSTER set is publicly available at https://doi.org/10.5281/zenodo.12658320, representing a stable and versioned data resource. The Python scripts are available at https://github.com/rareylab/LOBSTER, open-source, and allow for updating or recreating superposition sets with different data sources. Graphical abstractSimplified illustration of the LOBSTER dataset generation.

Comparative Analysis of Silicone Mouth Swabs with Varying Hardness Levels for Optimal Plaque Removal in Elderly Oral Care.

Silicone mouth swabs have emerged as a promising alternative to gauze, sponge brushes, and soft-bristled toothbrushes, offering a balance between gentle cleaning and effectiveness. The flexibility and softness of silicone make it a suitable material for safely cleaning the sensitive oral tissues of elderly patients. This study aims to determine the optimal hardness level of silicone that maximises cleaning effectiveness while minimising the risk of trauma to oral tissues. A pseudo-plaque was created by mixing 6.0 g of Thicken Up Clear food additive with 12.0 ml of water and food colouring, which was then spread onto a NISSIN dentoform silicone rubber sheet (simulated soft tissue) with a thickness of 2.0 mm. Silicone heads with different hardness levels - 20, 30, 40, 50, and 60 Shore A - were attached to a V.P.2000 tooth brushing machine, operating at 75 rounds per minute with a force of 1.96 N. Each swab was used to brush the surface 25 times (n = 16 for each group). A one-way analysis of variance (ANOVA) revealed a statistically significant difference in pseudo-plaque removal among the five hardness levels, with an F-value of 106.161 (degrees of freedom = 4, 75, p 0.001). The Games-Howell pairwise comparison test showed that all five silicone hardness levels differed significantly from each other in their effectiveness in removing pseudo-plaque (p 0.05). No visible simulated soft tissue damage was observed before and after brushing, as inspected with a stereomicroscope in all experiments. The silicone oral swab with a hardness level of 60 Shore A was found to maximise pseudo-plaque removal in vitro. This finding is crucial for the development of specialised oral hygiene tools tailored to the needs of the elderly population, thereby enhancing oral health and overall well-being.

Assessing the association between cigarette smoking and blood C-reactive protein levels using restructured cohort data

IntroductionCigarette smoke exposure is known to induce inflammation, leading to elevated levels of inflammatory markers such as white blood cell (WBC) count and C-reactive protein (CRP). Despite extensive research on this relationship, longitudinal studies are limited. We aimed to explore the association between cigarette smoke exposure and WBC count and CRP levels by restructuring community cohort data. MethodsData from a community cohort of the Korean population, followed biennially from 2001 to 2018, were utilized. Smoking status was determined through self-administered questionnaires. WBC and CRP levels were measured in a central laboratory with stringent quality control. Cohort data were restructured into pairs representing before and after measurements. We analyzed smoking effects on WBC and CRP using pairwise before-after tests based on changes in smoking status. Furthermore, parallel group analyses comparing changes in smoking status to no change were conducted. ResultsAnalysis included 4336 pairs for WBC and 3068 pairs for CRP from 10,030 participants. Pairwise analysis showed a significant decrease in WBC transitioning from current smoker to non-smoker and an increase from non-smoker to current smoker. Parallel group analysis demonstrated a significant decrease in WBC transitioning from current smoker to non-smoker compared to remaining current smoker, and an increase from non-smoker to current smoker compared to remaining non-smoker. CRP did not exhibit significant associations in either analysis. ConclusionsIn a community cohort, cigarette smoking was associated with elevated WBC count. However, CRP levels did not consistently reflect inflammation associated with cigarette smoking.

Utilization of Glucagon-Like Peptide-1 Receptor Agonist at the Time of Total Hip Arthroplasty for Patients Who Have Morbid Obesity.

Morbid obesity negatively affects outcomes after total hip arthroplasty (THA). The optimal strategy for weight loss before THA has not been identified. Recently, glucagon-like peptide-1 receptor agonists (GLP-1 RA) have become increasingly popular as an effective pharmacologic weight loss agent. The goal of this study was to evaluate the effect of perioperative GLP-1 RA use in patients who have morbid obesity undergoing primary THA on postoperative outcomes. Using an administrative claims database, patients who had morbid obesity (body mass index [BMI] ≥ 40.0) undergoing primary THA were identified. Patients who had morbid obesity and GLP-1 RA use for three months before and after surgery (treatment) were matched to patients who had morbid obesity without GLP-1 RA use (control) and to a comparison group of patients who had severe obesity (BMI = 35.0 to 39.9) in a 1:4:4 ratio, resulting in 771, 3,084, and 3,084 patients in the treatment, control, and severe obesity comparison group, respectively. Overall group differences in 90-day and 2-year postoperative outcomes were compared using univariable tests, followed by post hoc pairwise testing and P-value adjustment. Patients who had morbid obesity on GLP-1 RA had a significantly lower rate of 90-day periprosthetic joint infection (PJI) (1.6 versus 3.2%; P = 0.03), readmission (6.9 versus 9.7%; P = 0.04), any medical complication (10.5 versus 14.1%; P = 0.03), and postoperative hematoma formation (0 versus 1.3%, P < 0.01) compared to controls. Patients who had morbid obesity on GLP-1 RA demonstrated lower rates of hematoma formation (0 versus 1.0%; P <0.01) compared to patients who had severe obesity (BMI = 35.0 to 39.9). There were no differences in 2-year surgical complications. Perioperative use of GLP-1 RA in patients who had morbid obesity is associated with reduced risk of acute PJI and 90-day hospital readmission. The risk is reduced to a level comparable to obese patients who have a BMI < 40.0. Randomized controlled trials are necessary to determine the true effect and mechanism of action.

Effects of material and structure types on drifting speed of fish aggregation devices (FADs) in tuna purse seine fishery

The drifting speed and trajectory of fish aggregation devices (FADs) influence tuna aggregation behavior. Based on expertise, fishermen modify FAD structures to slow down drifting speed, but few studies quantify material and structure effects on this speed. To address this, 14 different types of FAD models were tested under 5 different current velocities in a flume tank and compared drifting using pairwise Wilcoxon tests. Results indicate that 1) FAD models covered with netting exhibited higher drifting speeds than the others. 2) It is feasible that replacing the netting bundle with the cotton rope of the same diameter for constructing submerged structure effectively slows down the drifting speeds of FADs. 3) Additionally, FAD models with a floating structure aspect ratio close to 1 exhibited slower drifting speeds compared to other designs when the submerged structure is the same.

Towards Carbon Neutrality: The Impact of Private AI Investment and Financial Development in the United States – An Empirical Study Using the STIRPAT Model

This investigation analyses the influence of private AI investment and financial development (FD) on CO2 emissions in the United States, using the STIRPAT framework to account for the functions of GDP, population, and foreign direct investment (FDI). The data's robustness was verified through the application of a variety of unit root tests, which confirmed that the variables are free of unit root issues and exhibit a varied order of integration. The ARDL bound test was used to investigate the cointegration among the variables and it found a long-run equilibrium relationship. The ARDL model results show that income, FDI, FD, and population significantly increase CO2 emissions in both the short and long term. In contrast, we found that private investment in AI led to a significant reduction in CO2 emissions over these time frames. Additional estimations were conducted using FMOLS, DOLS, and CCR methods to verify the ARDL results, all of which attested to the initial findings' robustness. In addition, the study implemented a pairwise Granger causality test to illustrate the directional relationships between the variables. There is a unidirectional causal link between GDP, private AI investment, FDI, population, and CO2 emissions, according to the findings. Most notably, we observed bidirectional causality between CO2 emissions and FD. Diagnostic tests further corroborated the validity of the study's conclusions, confirming that the model is free from specification errors, serial correlation, and heteroscedasticity.

Market Integration of Domestic and International Cotton Prices

Market integration is perceived as a precondition for effective market reform in developing countries. The current study on cointegration analysis was taken up to analyse how different spatially separated cotton markets are inter-connected and impact the price change in one market on other markets. Monthly prices for the period January 2010 to February 2024 from the markets viz., Cotlook-A Index, Chinese spot market, Rajkot in Gujarat, Hinganghat in Maharashtra, Adilabad and Warangal in Telangana were used for the analysis. Augmented Dickey-Fuller (ADF), Johansen's multivariate Cointegration approach, Granger causality test, and Vector Error Correction Model (VECM) were used to test the study the long-run spatial integration. The study confirmed the presence of market cointegration. The pair-wise Granger causality test identified the bidirectional and unidirectional relationship between markets chosen. Cotlook A- Index, China and Adilabad markets affected most of the markets unidirectionally and acted as lead markets. The VECM inferred that China, Rajkot and Hinganghat markets attained equilibrium rapidly in short run. Thus, the cotton markets were highly integrated in India. Thus, Stabilizing the prices in one market would influence the other markets improving competitiveness and market efficiency.

Abstract B063: DiMMER: A robust computational pipeline for differential methylation marker evaluation in R of cell-free DNA fragments

Abstract Background: Decoding the origins of cell-free DNA (cfDNA) released from dying cells in a liquid biopsy sample offers the potential to provide insight into the dynamic, organism-wide changes reflective of health and disease, making cfDNA an ideal target for serial, minimally invasive monitoring of disease-related changes. To this end, cell-type specific DNA methylation patterns offer a promising target to facilitate tissue of origin analysis, yet limited methods exist to identify differentially methylated regions that distinguish cell-types. Methods: We develop a robust differentially methylated marker region identification pipeline, DiMMER, that leverages cfDNA fragment level information of neighboring, co-regulated CpG sites on methylome-wide sequencing reads. Compared to prior methods that utilize simple heuristics in one-vs-all average methylation rate comparisons, we implement an individual pairwise statistical test procedure across all cell-types or groups under consideration. We assess the cell-specific nature of identified differentially methylated marker regions by generating in-silico mixtures from known cell-type of origin at each region, and calculating the area under the receiver operating characteristic curve (AUROC). We utilize our differentially methylated marker finding pipeline to identify melanocyte specific methylation marker regions and assess their functional role through annotations. We show these cell-specific regions are conserved in melanoma cell-lines and are distinct from the aberrant changes in a cancer context. Results: We identified the most cell-type specific differentially methylated marker regions across 24 distinct cell-type groups using our pipeline. Compared to a simpler one-vs-all heuristic, we demonstrate improved cell-type specificity evidenced by a higher AUROC on average. Using our pipeline we identified melanocyte-specific marker regions, which were commonly found in intronic and promoter regions of genes related to melanocyte development and differentiation. When comparing methylation patterns between melanocytes and melanoma cell-lines, we demonstrate melanocyte specific methylation marks are conserved through the transformation to malignant melanoma. Conclusion: As methylome-wide sequencing methods continue to rapidly develop and more cell-specific methylation data is generated, there is unmet need for more statistically robust differentially methylated marker finding tools. Here we present one such tool, DiMMER, and demonstrate the potential utility of identifying such regions to be used to assess organ-specific load as a measure of residual disease, as opposed to traditional circulating tumor DNA quanitification. Citation Format: Arthur P McDeed, Sidharth S Jain, Megan E McNamara, Amber Alley, Anton Wellstein, Jaeil Ahn. DiMMER: A robust computational pipeline for differential methylation marker evaluation in R of cell-free DNA fragments [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B063.

Navigating Carbon Peaking and Neutrality in MENA: The Impact of Foreign Direct Investment and Trade Openness Using Panel PCSE and FGLS Techniques

ABSTRACTIn response to the global challenge of climate change and the drive towards carbon neutrality, this study investigates the effects of foreign direct investment (FDI) and trade openness (TO) on carbon emissions (CEM) within the Middle East and North Africa (MENA) region. The research spans 18 countries from 1990 to 2022, focusing on Sustainable Development Goal 13. Utilizing Porter's hypothesis and the Environmental Kuznets Curve (EKC) theory, the study applies quantitative methods including panel corrected standard errors (PCSE) and feasible generalized least squares (FGLS) to ensure robustness. To address potential endogeneity, two‐stage least squares and lagged effect estimations are employed. The findings reveal that both FDI and TO are associated with reduced CEM, indicating positive environmental impacts. Also, the pairwise causality tests show bidirectional causality between FDI, TO, and CEM, while a unidirectional causality is found from industrialization (IND) and energy consumption (EC) to CEM. These results underscore the importance of integrating FDI and TO into strategies for achieving carbon neutrality and advancing sustainable development goals, offering actionable insights for policymakers.

Three New Species and Five New Host Records from Chaetomiaceae with Anti-Phytopathogenic Potential from Cover Crops Astragalus sinicus and Vicia villosa.

Cover crops, typically planted during off-seasons and requiring less agronomic manipulation, may provide abundant fungal resources. Certain species of Chaetomiaceae could serve as potential agents for controlling plant diseases and developing bioorganic fertilizers. Eight species from five genera of Chaetomiaceae were identified from healthy Astragalus sinicus and Vicia villosa, two major cover crops, through multigene phylogenetic analysis, morphological identification, and pairwise homoplasy index testing. The identified species comprise three new species: Achaetomium astragali, Subramaniula henanensis, and S. sichuanensis, as well as five known but new host record species: Botryotrichum murorum, Chaetomium coarctatum, C. pseudocochliodes, C. pseudoglobosum, and Collariella pachypodioides. Dual culture tests revealed that isolates of all eight Chaetomiaceae species exhibited antagonistic effects on multiple phytopathogens. Among the identified fungi, the NSJA2 isolate, belonging to C. coarctatum, exhibited significant relative inhibition effects on 14 out of 15 phytopathogens tested in this study, indicating its broad-spectrum antagonistic effects. Additionally, NSJA2 exhibited excellent salt tolerance. Overall, our study has identified multiple fungi with anti-phytopathogens potential, among which NSJA2 exhibits high potential for practical application. This finding paves the way for further exploration and exploitation of NSJA2 as a promising biocontrol agent.

Clinical Variant Reclassification in Hereditary Disease Genetic Testing

Because accurate and consistent classification of DNA sequence variants is fundamental to germline genetic testing, understanding patterns of initial variant classification (VC) and subsequent reclassification from large-scale, empirical data can help improve VC methods, promote equity among race, ethnicity, and ancestry (REA) groups, and provide insights to inform clinical practice. To measure the degree to which initial VCs met certainty thresholds set by professional guidelines and quantify the rates of, the factors associated with, and the impact of reclassification among more than 2 million variants. This cohort study used clinical multigene panel and exome sequencing data from diagnostic testing for hereditary disorders, carrier screening, or preventive genetic screening from individuals for whom genetic testing was performed between January 1, 2015, and June 30, 2023. DNA variants were classified into 1 of 5 categories: benign, likely benign, variant of uncertain significance (VUS), likely pathogenic, or pathogenic. The main outcomes were accuracy of classifications, rates and directions of reclassifications, evidence contributing to reclassifications, and their impact across different clinical areas and REA groups. One-way analysis of variance followed by post hoc pairwise Tukey honest significant difference tests were used to analyze differences among means, and pairwise Pearson χ2 tests with Bonferroni corrections were used to compare categorical variables among groups. The cohort comprised 3 272 035 individuals (median [range] age, 44 [0-89] years; 2 240 506 female [68.47%] and 1 030 729 male [31.50%]; 216 752 Black [6.62%]; 336 414 Hispanic [10.28%]; 1 804 273 White [55.14%]). Among 2 051 736 variants observed over 8 years in this cohort, 94 453 (4.60%) were reclassified. Some variants were reclassified more than once, resulting in 105 172 total reclassification events. The majority (64 752 events [61.65%]) were changes from VUS to either likely benign, benign, likely pathogenic, or pathogenic categories. An additional 37.66% of reclassifications (39 608 events) were gains in classification certainty to terminal categories (ie, likely benign to benign and likely pathogenic to pathogenic). Only a small fraction (663 events [0.63%]) moved toward less certainty, or very rarely (61 events [0.06%]) were classification reversals. When normalized by the number of individuals tested, VUS reclassification rates were higher among specific underrepresented REA populations (Ashkenazi Jewish, Asian, Black, Hispanic, Pacific Islander, and Sephardic Jewish). Approximately one-half of VUS reclassifications (37 074 of 64 840 events [57.18%]) resulted from improved use of data from computational modeling. In this cohort study of individuals undergoing genetic testing, the empirically estimated accuracy of pathogenic, likely pathogenic, benign, and likely benign classifications exceeded the certainty thresholds set by current VC guidelines, suggesting the need to reevaluate definitions of these classifications. The relative contribution of various strategies to resolve VUS, including emerging machine learning-based computational methods, RNA analysis, and cascade family testing, provides useful insights that can be applied toward further improving VC methods, reducing the rate of VUS, and generating more definitive results for patients.

Evaluating the effects of silent genes on pairwise kinship testing

Short tandem repeat (STR) loci are frequently utilized in kinship testing, and mutations of a single base occurring in the primer-binding region of the STR locus can result in the failure of allelic amplification and the emergence of silent genes. Silent genes are not observable and, therefore, are excluded from the genotypes assessed. Pedigree likelihood ratios (LRs) are often employed in kinship testing to determine the likelihood of different kinship scenarios. LR values are derived from various types of genotypes. LRexact values are based on the exact or actual genotypes, which may include silent genes. Conversely, LRobserve values are based on observed genotypes that exclude silent genes, while LRadjust values incorporate all potential genotypes, including both observed and those with silent genes. Initially, the formulae for LRs in 1st degree, 2nd degree, and 3rd degree kinship testing are presented according to different genotype forms of pairwise individuals. The correctness of these formulae is then verified using the Familias software, and the results are compared with those from the GeneVisa software (www.genevisa.net). Lastly, the simulation modules of GeneVisa are used to assess the impact of silent genes on pairwise kinship testing. The findings indicate that the overall impact of silent genes is minimal, although in some cases, the effects can be relatively significant. The influence of silent genes generally decreases as the kinship relationship becomes more distant. In specific kinship tests, the effect of silent genes is reduced when the individuals are unrelated compared to when there is a kinship relationship. Utilizing the LRadjust value for 1st degree and 2nd degree kinship testing can substantially mitigate the effects of silent genes.

Radiotherapy as a metastasis directed therapy for liver oligometastases - comparative analysis between CT-guided interstitial HDR brachytherapy and two SBRT modalities performed on double-layer and single layer LINACs.

Surgical resection is gold standard for treatment of liver metastasis, locally ablative techniques including computer tomography (CT)-guided interstitial high-dose-rate (HDR) brachytherapy (CT-BRT) and stereotactic body radiotherapy (SBRT) have gained prominence as alternatives, offering comparable outcomes in selected patients. We aim to compare CT-BRT and SBRT - based on dosimetric analysis. Patients who underwent CT-BRT for oligometastatic, ≤4cm liver metastases between 2018 and 2024 were eligible. SBRT plans for Halcyon (SBRTh) and TrueBeam (SBRTtb) were prepared virtually. In the CT-BRT group CTV was equal to PTV, for SBRTh and SBRTtb planning, a 5mm margin was applied to CTV to create PTV. Dose calculation was carried out with the TG-43 algorithm for CT-BRT and Anisotropic Analytical Algorithm for SBRTh and SBRTtb group. Descriptive statistics were used to compare the data. The Wilcoxon pairwise order test was utilized to compare dependent groups. CT-BRT resulted in a more favorable dose distribution within PTVs for Dmean, D50, and D90, while SBRT showed better results for D98 and V27.5Gy. No significant differences were observed for V25Gy between CT-BRT and SBRTtb, but SBRTh favored over CT-BRT. For OARs, CT-BRT plans showed better values for V5, V10, and V11.6Gy in the uninvolved liver volume. There were no significant differences in dose distribution for the duodenum, bowel, and heart. SBRT modalities performed better in the kidney. CT-BRT had improved dose distribution in the esophagus, great vessels, ribs, skin, spinal cord, and stomach compared to SBRT. CT-BRT could be a viable alternative to SBRT for certain patients with liver malignancies.

Saturation transfer (CEST and MT) MRI for characterization of U-87 MG glioma in the rat.

The focus of this work was to identify the optimal magnetic resonance imaging (MRI) contrast between orthotopic U-87 MG tumours and normal appearing brain with the eventual goal of treatment response monitoring. U-87 MG human glioblastoma cells were injected into the brain of RNU nude rats (n= 9). The rats were imaged at 7T at three timepoints for all animals: 3-5, 7-9, and 11-13 days after implantation. Whole-brain T1-weighted (before and after gadolinium contrast agent injection), diffusion, and fluid-attenuated inversion recovery scans were performed. In addition, single-slice saturation-transfer-weighted chemical exchange saturation transfer (CEST), magnetization transfer (MT), and water saturation shift referencing (WASSR) contrast Z-spectra and T1 and T2 maps were also acquired. The MT and WASSR Z-spectra and T1 map were fitted to a two-pool quantitative MT model to estimate the T2 of the free and macromolecular-bound water molecules, the relative macromolecular pool size (M0, MT), and the magnetization exchange rate from the macromolecular pool to the free pool (RMT). The T1-corrected apparent exchange-dependent relaxation (AREX) metric to isolate the CEST contributions was also calculated. The lesion on M0, MT and AREX maps with a B1 of 2μT best matched the hyperintensity on the post-contrast T1-weighted image. There was also good separation in Z-spectra between the lesion and contralateral cortex in the 2-μT CEST and 3- and 5-μT MT Z-spectra at all time points. A pairwise Wilcoxon signed-rank tests with Holm-Bonferroni adjustment on MRI parameters was performed and the differences between enhancing lesion and contralateral cortex for the MT ratio with 2μT saturation at 3.6ppm frequency offset (corresponding to the amide chemical group) and M0, MT were both strongly significant (p< 0.001) at all time points. This work has identified that differences between enhancing lesion and contralateral cortex are strongest in MTR with B1=2μT at 3.6ppm and relative macromolecular pool size (M0, MT) images over entire period of 3-13 days after cancer cell implantation.