Strong Consistency Research Articles

Validation of a holistic composite outcome measure for the evaluation of chronic pain interventions.

Chronic pain is a personal experience influenced by multiple biopsychosocial factors. Using a pain intensity measure alone to assess the effectiveness of a chronic pain intervention fails to fully evaluate its impact on the multifaceted chronic pain experience. The holistic minimal clinically important difference (MCID) is a composite outcome developed to provide a comprehensive assessment of chronic pain in response to intervention, across 5 outcome domains: pain intensity, health-related quality of life, sleep quality, physical, and emotional function. To focus on domains where the individual need is greatest, the holistic MCID reflects the cumulative MCID averaged over only the domains where subjects were impaired preintervention. To assess the internal and construct validity of the Holistic MCID score to inform its future use as an evidence-based tool. This validation study was undertaken using data from the EVOKE trial with 111 patients up to 24-month follow-up. Internal consistency of the holistic MCID was assessed using Cronbach alpha statistic and dimensional exploration using principal component analysis. The holistic MCID measure demonstrated strong internal consistency with Cronbach alpha >0.7 at all follow-ups. Principal component analysis showed one overarching holistic dimension to be present in the composite. Construct validity was demonstrated by an increase in the holistic MCID score being associated with both increased Patients' Global Impression of Change, EuroQol visual analogue scale score, and each of the outcome domains in a "leave-one-out" analysis (all P < 0.001). The holistic MCID provides a valid measure for the comprehensive, personalized assessment of response after a chronic pain intervention. The validity of the holistic MCID requires further confirmation in other chronic pain populations and with different interventions.

Competitive water adsorption for low-energy desalination: Insights from statistical physics theory

In this research, the statistical physics theory has been deployed to unlock the mysteries of water molecule binding on Zeolite and Silica Gel at the microscopic level. The adopted computational procedure, based on the grand canonical partition function, provided physical insights of the docking mechanism by scrutinizing the stereographic and energetic variables. The number of receiving sites, their densities, the saturation amount and the energetic factors were assessed due to the strong consistency between the numerical and experimental results. Docking inspections revealed that H2O primarily adopted a non-parallel orientation upon interaction with the adsorbent receptor sites. The estimated attachment energies ranged from 18.25 kJ/mol to 24.55 kJ/mol indicating a physisorption process where weak forces (van der Waals) mainly govern the surface occupancy. Desalination effectiveness has been examined and according to calculations the coefficient of performance (COP) and the quantitative efficiency metric (QEM) is 2.7 times and 1.2 times respectively greater in case of Zeolite than Silica Gel. By analyzing pore size distribution (PSD) and adhesion energy distribution (AED), this study elucidates the relationship between pore size and target molecule capture, and predicts binding strength and potential for molecule capture/release under various conditions.

FAIR data management: a framework for fostering data literacy in biomedical sciences education.

Data literacy, the ability to understand and effectively communicate with data, is crucial for researchers to interpret and validate data. However, low reproducibility in biomedical research is nowadays a significant issue, with major implications for scientific progress and the reliability of findings. Recognizing this, funding bodies such as the European Commission emphasize the importance of regular data management practices to enhance reproducibility. Establishing a standardized framework for statistical methods and data analysis is essential to minimize biases and inaccuracies. The FAIR principles (Findable, Accessible, Interoperable, Reusable) aim to enhance data interoperability and reusability, promoting transparent and ethical data practices. The study presented here aimed to train postgraduate students at the Universidad Europea de Madrid in data literacy skills and FAIR principles, assessing their application in master thesis projects. A total of 46 participants, including students and mentors, were involved in the study during the 2022-2023 academic year. Students were trained to prioritize FAIR data sources and implement Data Management Plans (DMPs) during their master's thesis. An 11-item questionnaire was developed to evaluate the FAIRness of research data, showing strong internal consistency. The study found that integrating FAIR principles into educational curricula is crucial for enhancing research reproducibility and transparency. This approach equips future researchers with essential skills for navigating a data-driven scientific environment and contributes to advancing scientific knowledge.

Instruments for Measuring the Burden of Family Caregivers of Cancer Patients: A Systematic Review of Measurement Properties.

This study identifies instruments for assessing the burden on family caregivers of cancer patients and evaluates their psychometric properties using COSMIN criteria. A systematic review based on COSMIN methodology. The review adhered to PRISMA guidelines. Relevant studies were identified through searches in PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure, Wanfang Database, and China Science and Technology Journal Database, covering literature from inception to September 2024. Included studies focused on developing or validating measurement tools and assessing psychometric properties such as reliability, internal consistency and construct validity. Two independent researchers screened the literature, extracted data and evaluated psychometric properties using COSMIN criteria while assessing evidence quality via the GRADE method. A total of 32 studies were included, encompassing 17 tools for assessing caregiver burden. None reported measurement error, cross-cultural validity or responsiveness. The Caregiver's Burden Scale in End-of-Life Care (CBS-EOLC) demonstrated strong reliability, validity and internal consistency, receiving a strong recommendation for clinical practice. In contrast, the Zarit Burden Interview (ZBI), Family Caregiver Burden Interview Scale (FBIS) and Bakas Caregiving Outcomes Scale (BCOS) are not recommended due to insufficient supporting evidence. Other tools showed weak evidence, leading to weak recommendations. The CBS-EOLC exhibits comprehensive psychometric properties suitable for clinical applications. The ZBI, FBIS and BCOS lack adequate supporting evidence and are not recommended. Future research should focus on measurement error, cross-cultural validity and responsiveness to enhance these tools' applicability and reliability. This review provides evidence for healthcare providers to select instruments for assessing caregiver burden in cancer patients. This systematic review highlights the need for comprehensive assessments of caregiver burden based on COSMIN guidelines. This study is a systematic review with no patient or public participation.

The Toxic Masculinity Scale: Development and Initial Validation

The present study sought to develop and validate the Toxic Masculinity Scale (TMS). Following scale development best practices, a thorough review of the literature and existing measures was conducted. Next, a qualitative inquiry using a grounded theory approach was employed to develop a data-driven definition of toxic masculinity and 165 proposed instrument items. These items were reviewed and modified with input from content experts (N = 6). The initial 108 items were administered to a preliminary sample (N = 683) of U.S. White undergraduate men. Exploratory factor analysis indicated a five-factor structure (i.e., Masculine Superiority, Gender Rigidity, Emotional Restriction, Repressed Suffering, Domination and Desire). Item analysis yielded a 35-item five factor survey that was administered to a second novel sample (N = 408) of White undergraduate men. A confirmatory factor analysis indicated inadequate fit for the 35-item scale; however, fit was improved by reducing scale length to 28 items loading onto 4 factors (removal of the Domination and Desire factor). Internal consistency reliability, construct validity, and discriminant validity were explored with this sample. The TMS28 demonstrated strong positive correlations with related measures (e.g., CMNI, MRNI) and a strong negative correlation with a diametrically opposed measure (i.e., LFAIS). Additionally, the TMS28 demonstrated strong adequate internal consistency for the scale overall (α = 0.93) and for the four subscales (i.e., α = 0.87–0.94). Future directions and implications for the instrument are discussed.

Reconstruction of 30 m Land Cover in the Qilian Mountains from 1980 to 1990 Based on Super-Resolution Generative Adversarial Networks

Long time series of annual land cover with fine spatio-temporal resolutions play a crucial role in studying environmental climate change, biophysical modeling, carbon cycling models, and land management. Despite a strong consistency exhibited by several publicly available medium to fine resolution global land cover datasets, significant discrepancies exist at the regional scale; moreover, only every 5/10 year land cover were available. Consequently, high-quality annual land cover datasets before 2000 are unavailable in China. In this study, we proposed a deep learning-based method by integrating multiple remote sensing data from different platforms with historical high spatial resolution land cover datasets (CNLUCC) to derive the 30 m annual land cover maps from 1980 to 1990 for Qilian Mountain. First, the super-resolution generative adversarial network models for upscaling the 5.5 km AVHRR NDVI to 250 m were established by employing the AVHRR and MODIS NDVI data with the same year as input, and the early time series AVHRR NDVI data were subsequently upscaled to 250 m through the above models. Second, the breaks for the additive seasonal and trend (BFAST) change detection algorithm was applied to the upscaled time series NDVI data to detect the change time of different land cover types. Third, the CNLUCC data in 1980 and 1990 were updated to annual land cover datasets from 1980 to 1990 and the annual mapping results provided insights into the dynamic processes of urbanization, deforestation, water bodies, and farmland from 1980 to 1990. Finally, comprehensive analysis and validation were carried out for evaluation and an overall accuracy of 77.26% for the land cover product in 1986 was achieved.

Development and validation of survival nomograms for patients with anaplastic thyroid carcinoma: a SEER program-based study.

We aimed to study the prognostic risk factors affecting patients with anaplastic thyroid carcinoma (ATC), develop a clinical prognostic model, and assess patient survival outcomes. Patients with anaplastic thyroid carcinoma from 2000 to 2019 were selected from the Surveillance, Epidemiology, and End Results (SEER) Program to extract the clinical variables used for analysis. The dataset was divided into training (70%) and validation (30%) sets based on a 7:3 ratio. Univariate and LASSO regression analyses were performed on clinical variables from the training set to identify independent prognostic factors. Independent prognostic factors were determined by Univariate and lasso regression according to the clinical variables of the training set, and a nomogram model was established to construct a prognostic model based on the contribution degree of the predictors. The prognostic model was evaluated and internally verified by C-index, ROC curve and calibration curve. A total of 713 ATC patients were included in the SEER database. LASSO regression results indicated that age, marital status, race, tumor size, whether the primary lesion was limited to the thyroid gland, surgery, radiotherapy and chemotherapy, were associated with overall survival(OS) prognosis of ATC, and were used to construct nomograms. In the training cohort, the OS nomogram's C-index was 0.708 (95% CI 0.672-0.745); in the internal validation cohort, the C-index was 0.677 (95% CI 0.620-0.735). ROC curves demonstrated that the OS nomogram exhibits excellent predictive accuracy and discriminative ability. Calibration curves indicated strong consistency between the OS nomogram's predicted survival rates and actual survival rates. We established a survival prediction model for ATC, which can assist clinicians in assessing patient prognosis and making personalized treatment decisions.

Cultural Adaptation and Psychometric Properties of the Spanish Version of the Gay Affirmative Practice Scale (GAP-ES)

Background/Objectives: Lesbian, gay, bisexual, and transgender (LGBT) individuals often face discrimination in healthcare settings, resulting in health disparities. Evaluating healthcare professionals’ affirmative practices is essential for promoting inclusive care and addressing these disparities. The aim of this study was to assess the psychometric properties of the Spanish version of the Gay Affirmative Practice Scale (GAP-ES), which measures healthcare professionals’ affirmative practices towards gay individuals. Methods: Before assessing its psychometric properties, the original Gay Affirmative Practice Scale (GAP) was translated and culturally adapted from English to Spanish. Following the translation, the psychometric properties were tested on a sample of 236 healthcare professionals. The internal consistency of the questionnaire was measured using Cronbach’s alpha and the discriminatory power index. Factor structure was evaluated with Confirmatory Factor Analysis (CFA) using the Diagonally Weighted Least Squares method. Results: The sample consisted of 152 female (64.41%) and 84 male (35.59%) participants, with 58.05% identifying as heterosexual, 28.81% as homosexual, and 13.14% as bisexual. The internal consistency of the GAP-ES was strong, with Cronbach’s alpha values of 0.915 for the Beliefs subscale and 0.902 for the Behaviors subscale. The McDonald’s Omega coefficient was 0.942, indicating high reliability. CFA confirmed a two-factor structure with satisfactory fit indices (CFI = 0.999, RMSEA = 0.071). Conclusions: The GAP-ES demonstrates strong internal consistency and a stable factor structure. It is a reliable tool for evaluating affirmative practices toward LGBT patients in Spanish-speaking healthcare contexts, supporting improved care for this population. The integration of the GAP-ES into clinical practice and training programs may support the enhancement of cultural competence among healthcare professionals, contributing to the reduction of health disparities for LGBT patients in Spanish-speaking settings.

Adaptation and psychometric evaluation of the breastfeeding self-efficacy scale to assess exclusive breastfeeding: a cross-sectional study in rural China.

Despite the benefits of exclusive breastfeeding, the proportion of exclusively breastfed children remains low in rural China. Self-efficacy is one of the most crucial modifiable factors predicting breastfeeding behavior. However, existing instruments in China do not specifically measure self-efficacy for exclusive breastfeeding but rather measure self-efficacy for any breastfeeding. Furthermore, they have been validated only in high-income Chinese settings. We sought to adapt and validate an instrument to measure exclusive breastfeeding self-efficacy within rural Chinese contexts. We introduced relevant items to Dennis' Breastfeeding Self-Efficacy Scale-Short Form (BSES-SF), which can assess maternal self-efficacy for exclusive breastfeeding. It was then implemented in a multistage random cluster sampling design and cross-sectional survey with home-visit interviews among women 0-6 months postpartum (n = 654) in the rural areas of four counties in Sichuan, China. We performed item-total and adjusted item-total correlations, as well as exploratory factor analysis to remove redundant items and determine the latent factor structure. We further applied confirmatory factor analysis to test the dimensionality of the scale. We then assessed the reliability of the scale and conducted tests of predictive and divergent validity. Known group comparisons were made by primiparous status and breastfeeding support level. We compared the validated Exclusive Breastfeeding Self-Efficacy Scale with the BSES-SF in terms of reliability and validity to explore the added value of scale modification. Our modification of the BSES-SF to target exclusive breastfeeding produced 19 items. This was further reduced to 15 items based on adjusted item-total correlations and exploratory factor analysis, forming the Exclusive Breastfeeding Self-Efficacy Scale. This scale had three dimensions: "Breast milk supply and quality," "Breastfeeding skills," and "Exclusive breastfeeding" subscales. The Exclusive Breastfeeding Self-Efficacy Scale demonstrated strong internal consistency and overall reliability with a Cronbach's alpha coefficient of 0.91. Predictive and divergent validity and known group comparison assessments supported its validity. Robust psychometric evaluations demonstrated enhanced validity and reliability compared to the original BSES-SF. Our Exclusive Breastfeeding Self-Efficacy Scale is valid and reliable for measuring exclusive breastfeeding self-efficacy within rural Chinese contexts and is ready for adaptation and validation for clinical and programmatic use elsewhere, particularly within LMICs.

Computation Models for Tsunami Wave Propagation using Extended Cellular Automata

Using traditional models to simulate the propagation of large-scale tsunami waves leads to low accuracy and low efficiency. To ensure higher timing accuracy of tsunami wave spread, built an enhanced model that connects cellular automata with an existing model of tsunami waves. To determine the ideal time step value, our approach considers how time steps affect simulation accuracy. The spread of tsunami waves using a two-dimensional cellular automata model was used to test the model. Extending cellular automata (CA) models for tsunami wave propagation involves incorporating additional complexity and realism to better simulate the dynamics of these natural phenomena. The findings indicate that 1/4 of the time required for all of the cellular material to be traversed is the ideal time step for the tsunami wave spread global cellular automata simulation program. With a mean accuracy of 86.78% and a mean Kappa coefficient of 0.6443, this model demonstrated strong temporal and spatial consistency when compared to historical tsunami wave data from NOAA. Combining the Kappa coefficient with extended cellular automata (ECA) can be beneficial in various applications, particularly those involving classification tasks or spatial modeling. The earliest arrival tsunami wave spread can be predicted and simulated using this approach.

Assessing Rodent Attitudes: The Psychometric Properties of the SARod in a Chilean Context

This study aimed to develop and validate the Scale of Attitudes towards Rodents (SARod) to measure public attitudes towards rodents in a Chilean community context. Utilizing an instrumental design, we gathered data from 497 participants using convenience sampling. The SARod, comprising 22 Likert-scale items, evaluates attitudes across four dimensions: Scientistic, Positivistic, Emotional Negativistic, and Cognitive and Behavioral Negativistic. An exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted to examine the scale’s structure and reliability, revealing strong internal consistency (Ω &gt; 0.8) across all factors. Results indicated that higher educational levels and increased interaction with rodents were associated with more positive attitudes, while a greater disposition towards rodent extermination correlated with more negative attitudes. No significant gender differences were observed. The SARod shows robust psychometric properties, offering a reliable tool for cross-cultural comparisons of rodent-related attitudes. This scale can inform targeted interventions and public education campaigns, promoting coexistence and effective rodent management strategies. Further research should explore the application of the SARod in diverse cultural contexts.

Local linear estimators for reflected diffusions

In this paper, we investigate the nonparametric local linear estimator for the drift function of reflected stochastic differential equations based on the discretely observed process. Under certain regularity conditions, we prove the strong consistency and establish the asymptotic normality for our proposed estimator. We also propose the optimal bandwidth selector for the estimator and show that the estimator does not have a boundary effect. Simulation results demonstrate that our method is superior to the method proposed by Cholaquidis et al. [Stat. Sin. 2021, 31: 29–51]. We apply the EUR/USD currency exchange rate data to illustrate our theoretical results.

QOL-10. AN ASSESSMENT TOOL FOR MEASURING CAREGIVERS’ DEATH ANXIETY IN PRIMARY BRAIN TUMOR: A CONFIRMATORY FACTOR ANALYSIS

Abstract BACKGROUND Caregivers of patients with primary brain tumor describe significant emotional distress regarding their loved one’s impending trajectory and eventual mortality—a construct known as death anxiety. Our team adapted a pre-existing, validated scale for patients with advanced cancer (the Death and Dying Distress Scale; DADDS) to measure this latent variable in caregivers of patients with primary brain tumors. Our adapted scale (DADDS-CG) demonstrated preliminarily strong internal consistency and construct validity. We now seek to confirm the factor structure, internal consistency, and convergent validity of the DADDS-CG in a second sample of neuro-oncology caregivers in accordance with best practices of measure development. METHODS Caregivers of those with primary brain tumors (N=221) completed an online battery of self-report questionnaires, including the 15-item Death and Dying Distress Scale-Caregiving (DADDS-CG), the Generalized Anxiety Disorder (GAD-7), and the Patient Health Questionnaire (PHQ-9). To verify the two-factor structure of the DADDS-CG, we used confirmatory factor analysis. Cronbach’s alpha measured internal consistency, Pearson correlations assessed convergent validity, and descriptive statistics determined the prevalence of death anxiety. RESULTS Caregivers (Mage=46.2) were primarily White (85.5%) female (72.4%) spouses (75.6%). The two-factor model demonstrated adequate fit (X2/df=4.24; CFI-.89; NFI=.87; RMSEA=.06), suggesting two correlated subscales of death anxiety: Finitude and Dying (r=.80). The DADDS-CG demonstrated strong internal consistency (a=.95) and was moderately correlated with the GAD-7 (r=.73) and PHQ-9 (r=.68), suggesting adequate convergent validity. Mean scores fell within the moderate range (M=40.5, SD=18.7), with 20.8%, 36.2%, and 43.0% of caregivers reporting low, moderate, and severe death anxiety, respectively. CONCLUSION The DADDS-CG is a valid and reliable assessment tool for measuring death anxiety in caregivers of those with primary brain tumors. Given the high prevalence of death anxiety, future investigations are needed to understand caregiver’s death anxiety throughout the disease trajectory and to inform intervention development for neuro-oncology caregivers.

Modification and Validation of the System Causability Scale Using AI-Based Therapeutic Recommendations for Urological Cancer Patients: A Basis for the Development of a Prospective Comparative Study

The integration of artificial intelligence, particularly Large Language Models (LLMs), has the potential to significantly enhance therapeutic decision-making in clinical oncology. Initial studies across various disciplines have demonstrated that LLM-based treatment recommendations can rival those of multidisciplinary tumor boards (MTBs); however, such data are currently lacking for urological cancers. This preparatory study establishes a robust methodological foundation for the forthcoming CONCORDIA trial, including the validation of the System Causability Scale (SCS) and its modified version (mSCS), as well as the selection of LLMs for urological cancer treatment recommendations based on recommendations from ChatGPT-4 and an MTB for 40 urological cancer scenarios. Both scales demonstrated strong validity, reliability (all aggregated Cohen’s K &gt; 0.74), and internal consistency (all Cronbach’s Alpha &gt; 0.9), with the mSCS showing superior reliability, internal consistency, and clinical applicability (p &lt; 0.01). Two Delphi processes were used to define the LLMs to be tested in the CONCORDIA study (ChatGPT-4 and Claude 3.5 Sonnet) and to establish the acceptable non-inferiority margin for LLM recommendations compared to MTB recommendations. The forthcoming ethics-approved and registered CONCORDIA non-inferiority trial will require 110 urological cancer scenarios, with an mSCS difference threshold of 0.15, a Bonferroni corrected alpha of 0.025, and a beta of 0.1. Blinded mSCS assessments of MTB recommendations will then be compared to those of the LLMs. In summary, this work establishes the necessary prerequisites prior to initiating the CONCORDIA study and validates a modified score with high applicability and reliability for this and future trials.

Centralized Data Warehouse vs. Data Mesh: A Comparative Analysis of Modern Data Management Paradigms

This comprehensive article explores the evolving landscape of enterprise data management, focusing on comparing traditional centralized data warehouses and the emerging data mesh paradigm. As organizations grapple with exponential data growth, projected to reach 180 zettabytes by 2025 [1], the choice of data architecture has become increasingly critical. The article examines both approaches' core principles, advantages, and challenges, highlighting how centralized data warehouses offer strong consistency and governance [2, 8] but face scalability issues [3]. In contrast, data mesh provides enhanced flexibility and domain-specific optimization [4] at the cost of more complex governance [5]. Through a detailed comparative analysis, the study investigates the impact of these architectures on organizational control, scalability, adaptability to business needs, and data quality management. Furthermore, it explores the potential of hybrid approaches that aim to leverage the strengths of both paradigms. The research considers various factors influencing the selection of data management strategies, including organization size, data complexity, and industry-specific requirements. By synthesizing current literature and industry trends, this article provides data professionals and decision-makers with a nuanced understanding of modern data management paradigms, enabling them to make informed choices aligned with their specific business contexts and long-term data strategies.

Speed-Dedup: A New Deduplication Framework for Enhanced Performance and Reduced Overhead in Scale-Out Storage

Conventional deduplication systems face critical challenges such as excessive write amplification, high read/write latency, and sub-optimal storage utilization. These limitations often undermine the performance benefits of deduplication by slowing down I/O acknowledgements due to amplified deduplication I/Os, excessive data chunk replication, and strict consistency requirements. To address these issues, we present Speed-Dedup, a novel deduplication framework that employs a deduplicated primary–semi-deduplicated replica object approach. This strategy reduces write amplification by restricting deduplication to the primary object while maintaining a semi-deduplicated replica object used for immediate read/write acknowledgements, thus enhancing I/O latency and storage efficiency. Speed-Dedup also replaces traditional strong consistency models with eventual consistency, allowing for non-blocking read operations and improving overall system throughput. Experimental results demonstrate that Speed-Dedup significantly outperforms traditional methods like GRATE and CAO, showing up to 21% improvement in I/O performance under low deduplication ratios and maintaining 14% or more gains under higher ratios. Additionally, write amplification is substantially reduced and latency improves by over 100% with faster recovery times during system failures. These findings highlight the effectiveness of Speed-Dedup as a scalable and efficient solution.

Diagnostic accuracy and image quality evaluation of ultrashort echo time MRI in the lungs.

This study evaluates the diagnostic accuracy of ultrashort echo time (UTE)-MRI for detecting pulmonary nodules and image quality. A total of 46 patients at our hospital underwent unenhanced computed tomography (CT) and UTE-MRI. The image quality and number of nodules detected using CT were used as the gold standards. Three diagnostic radiologists independently recorded the image quality (visibility and sharpness of normal anatomical structures) of the CT and UTE images and the number of pulmonary nodules detected. The diagnostic accuracy, subjective image quality, and consistency between observations were statistically analyzed. Among 46 patients, 36 (78.2%) had pulmonary nodules on CT images, whereas 10 patients (21.7%) had no pulmonary nodules. A total of 48 lung nodules were detected, 3 of which were ground-glass opacities. UTE-MRI revealed 46 lung nodules. Compared with CT, the sensitivity of all MRI readers for detecting lung lesions was 95.8%, and the 3-observer agreement was nearly perfect (P < .001, Kendall Wa [Kender Harmonious Coefficient] = 0.913). The overall image quality score of the observers was high, ranging from good to excellent, and the consistency of the subjective UTE-MRI image quality was good (Kendall Wa = 0.877, P < .001). For tracheal display, the subsegment of the bronchus was displayed, and the wall of the tube was clearly displayed. The difference in the Wa values between the observers was 0.804 (P < .001), indicating strong consistency. For blood vessels, subsegment blood vessels could also be displayed with clear walls and uniform signals (Kendal Wa = 0.823, P < .001), indicating strong consistency. Compared to CT, UTE-MRI can detect pulmonary nodules with a high detection rate, relatively good image quality, and strong consistency between observers. The development of UTE-MRI can provide a novel imaging method for the detection and follow-up of pulmonary nodules and diagnosis of pneumonia by reducing ionizing radiation.

Strain-level genomic analysis of serotype, genotype and virulence gene composition of group B streptococcus

IntroductionGBS (group B streptococcus) is an opportunistic pathogen that can colonize healthy individuals but presents significant challenges in clinical obstetrics and gynecology, as it can cause miscarriage, preterm birth, and invasive infections in newborns. To develop specific and personalized preventative strategies, a better understanding of the epidemiological characteristics and pathogenic features of GBS is essential.MethodsWe conducted a comprehensive strain-level genomic analysis of GBS, examining serotype and genotype distributions, as well as the composition and correlations of virulence genes using the blastn-short mode of the BLAST program(v2.10.0+), mlstsoftware (https://github.com/tseemann/mlst), Snippy (v4.6.0), FastTree (v2.1.11) and iTOL. The coding sequence region of virulence factors was annotated by Prodigal (v2.6.3) and Glimmer(v3.02b). We further identified host protein interacting with Srr2 by mass spectrometry analysis.ResultsWhile certain genotypes showed strong serotype consistency, there was no significant association between overall serotypes and genotypes. However, the composition of virulence genes was more closely related to the phylogeny of GBS, among which simultaneous presence of Srr2 and HygA exhibit significant association with hypervirulence. Tubulin emerged as the most distinct and abundant hit. The specific interaction of Tubulin with Srr2-BR, rather than Srr1-BR, was further confirmed by immunoblotting.DiscussionConsidering the impact of cytoskeleton rearrangement on GBS pathogenesis, this observation offers a plausible explanation for the hypervirulence triggered by Srr2. Collectively, our findings indicate that in the future clinical practice, virulence gene detection should be given more attention to achieve precise GBS surveillance and disease prevention.

Ocular Surface Disease Index Questionnaire (OSDI-Q), Unidimensionality, and Differential Item Functioning

Objective The OSDI-Q is a 12-item scale used instrument for DED prevalence, assess symptom severity, and impact on vision-related functioning. The research analysis investigates the precision, separation index and reliability of unidimensionality, and DEF, stratified by age and gender. The reliability analysis is to assess the internal consistency of the scale using Cronbach's α coefficient and McDonald's ω coefficient with item-rest correlations. Method 634 respondents took part in the OSDI questionaire. Rasch analysis was conducted using precision, separation index, and reliability for items and person, item and person fit statistics, assessing unidimensionality stratified by age and gender, and the use of SPSS to conduct the reliability analysis of the scale using analytical coefficients. Results The OSDI-Q items displayed robust reliability, with high PSI values of 7.63 and 0.98, respectively. Infit and outfit statistics were within acceptable ranges, explaining 39.90 % of variance. Differential item functioning was observed among the age groups involved. Additionally, the contrast in the principal component analysis of the unexplained variance exhibited an eigenvalue of 2.80 and a proportion of variance of 14%. DIF analysis showed significant differences for age groups of (16-26 years) and (27-40 years). The coefficients of Cronbach's and McDonald's are 0.85 for OSDI-Q demonstrated strong internal consistency. Conclusions OSDI-Q displayed appropriate infit and outfits. DIF analysis results of OSDI-Q of age group (16-26 years) performed better in poor vision while age group (27-40 years) performed better in areas with low humidity. Furthermore, the results of DIF analysis in males group performed better in driving at night, while the female group showed better performance in the questinaire. The OSDI-Q items scale reliability data for Cronbach's scale show high internal consistency and reliability. This research can help the medical communities to begin a better surge for medically integrated research.

SPIRIT: Scalable and Persistent In-Memory Indices for Real-Time Search

Today, real-time search over big microblogging data requires low indexing and query latency. Online services, therefore, prefer to host inverted indices in memory. Unfortunately, as datasets grow, indices grow proportionally, and with limited DRAM scaling, the main memory faces high pressure. Also, indices must be persisted on disks as building them is computationally intensive. Consequently, it becomes necessary to frequently move on-heap index segments to storage, slowing down indexing. Reading storage-resident index segments requires filesystem calls and disk accesses during query evaluation, leading to high and unpredictable tail latency. This work exploits hybrid DRAM and scalable non-volatile memory (NVM) to offer dynamically growing and instantly searchable (i.e., real-time) persistent indices in on-heap memory. We implement SPIRIT, a real-time text inversion engine over hybrid memory. SPIRIT exploits the byte-addressability of hybrid memory to enable direct access to the index on a pre-allocated heap, eliminating expensive block storage accesses and filesystem calls during live operation. It uses an in-memory segment descriptor table to offer: ① instant segment availability to query evaluators upon fresh ingestion, ② low-overhead segment movement across memory tiers transparent to query evaluators, and ③ decoupled segment movement into NVM from their visibility to query evaluators, enabling different policies for mitigating NVM latency. SPIRIT accelerates compaction with zero-copy merging. It supports volatile, graceful shutdown, and crash-consistent indexing modes. The latter two modes offer instant recovery using persistent pointers. SPIRIT with hybrid memory and strong crash consistency guarantees exhibits many orders of magnitude better tail response times and query throughout than the state-of-the-art Lucene search engine. Compared against a highly optimized non-real-time evaluation of Lucene with liberal DRAM size, on average, across six query workloads, SPIRIT still delivers 2.5 × better (real-time) query throughput. Our work applies to other services that will benefit from direct on-heap access to large persistent indices.