Browse Articles

Sex differences in physical activity dose-response effects on site-specific bone mineral density during childhood and adolescence

Identification of insertion sites for the integrative and conjugative element Tn916 in the Bacillus subtilis chromosome

Integrative and conjugative elements (ICEs) are found in many bacterial species and are mediators of horizontal gene transfer. Tn 916 is an ICE found in several Gram-positive genera, including Enterococcus , Staphylococcus , Streptococcus , and Clostridioides (previously Clostridium ). In contrast to the many ICEs that preferentially integrate into a single site, Tn 916 can integrate into many sites in the host chromosome. The consensus integration motif for Tn 916 , based on analyses of approximately 200 independent insertions, is an approximately 16 bp AT-rich sequence. Here, we describe the identification and mapping of approximately 10 5 independent Tn 916 insertions in the Bacillus subtilis chromosome. The insertions were distributed between 1,554 chromosomal sites, and approximately 99% of the insertions were in 303 sites and 65% were in only ten sites. One region, between ykuC and ykyB ( kre ), was a ‘hotspot’ for integration with ~22% of the insertions in that single location. In almost all of the top 99% of sites, Tn 916 was found with similar frequencies in both orientations relative to the chromosome and relative to the direction of transcription, with a few notable exceptions. Using the sequences of all insertion regions, we determined a consensus motif which is similar to that previously identified for C. difficile . The insertion sites are largely AT-rich, and some sites overlap with regions bound by the nucleoid-associated protein Rok, a functional analog of H-NS of Gram-negative bacteria. Rok functions as a negative regulator of at least some horizontally acquired genes. We found that the presence or absence of Rok had little or no effect on insertion site specificity of Tn 916 .

Enhancing strength and sustainability of concrete with steel slag aggregate

Abstract This study investigates the transformation of steel slag, a by-product of the steel industry, into a sustainable construction material by substituting it for natural aggregates in concrete mixtures. To this end, we have conducted an experimental program that evaluated 28 mix designs, along with a control mix based on natural aggregates, cement, silica fume, and chemical admixtures, to assess the effects of replacing natural aggregates with steel slag. Some mixes also incorporated different fiber types to enhance performance. The study assessed the mechanical and physical properties of both fresh and hardened concrete to evaluate the overall effects of these alterations. Furthermore, thermogravimetry-differential thermal analysis (TG-DTA) and X-ray diffraction (XRD) were employed to characterize the mineralogical composition and thermal behavior of the concrete mixes. To further validate the compressive strength improvements and quantify data variability, a statistical analysis was conducted. The results revealed that concrete mixtures utilizing steel slag demonstrated substantial enhancements in compressive strength, with four mixtures featuring complete replacement of natural aggregates achieving more than 1.7 times the strength of control mix. The inclusion of fibers further enhanced performance in terms of crack resistance and post-cracking behavior. The TG-DTA and XRD analyses revealed that the steel slag promotes additional hydration and the formation of calcium silicate hydrate, resulting in a denser microstructure. Furthermore, the statistical analyses confirmed that these improvements are statistically significant, highlighting the potential of steel slag and fiber reinforcement to enhance both the fresh and hardened properties of concrete. The current study demonstrated that steel slag can fully replace natural aggregates while enhancing concrete performance, offering a sustainable solution for both construction material sourcing and industrial waste management.

From blueprint to biobank: Leveraging expert recommendations for implementing change (ERIC) to pediatric cancer biobanking in Pakistan

Background In low- and middle-income countries, limited infrastructure and resources hinder biobank establishment, affecting specimen diversity. Addressing this gap is crucial for equitable health outcomes, as current databases are skewed towards Northern-European populations. In Pakistan, pediatric cancer biobanks are non-existent. Indus Hospital & Health Network (IHHN) in Karachi, with its large pediatric cancer unit, aims to establish a biobank to address region-specific pediatric cancer research needs. This manuscript describes the biobank implementation process using implementation science frameworks. Methods The pediatric cancer biobank at IHHN collects FFPE specimens for solid tumors, and isolated mononuclear cells from peripheral blood and bone marrow of suspected acute leukemia. Implementation planning workgroups included clinicians, EMR, IT, management, senior leadership, IRB, and external support from UNC and St. Jude Children’s Cancer Hospital. The selection of applicable ERIC (Expert Recommendations for Implementing Change) strategies through stakeholder workgroups considered scope, budget, and feasibility, and context. Standard protocols from ISBER and BCNet guided alignment with best practices. IHHN’s past experiences and tacit knowledge gained through rapid, successful implementation also facilitated strategy selection. The EPIS framework (exploration, preparation, implementation, sustainment) was used to map and organize the selected intervention strategies. Results Biobank implementation at IHHN, organized by EPIS stages, has been described through a set of 41 implementation strategies. Of these, 34 were selected out of 73 originally published ERIC strategies, while 7 were added based on contextually based workgroup consensus. 599 acute leukemia and 1137 solid tumor specimens have been banked since inception of the biobank operations 2 years earlier. The implementation activities and challenges described include infrastructure, swift specimen collection, prior to treatment, and informed consent. The ancillary processes including training and quality control have also been described and related data presented. Conclusion The implementation of Pakistan’s first acute leukemia biobank using ERIC and EPIS frameworks offers a structured approach beneficial for settings with limited biobanking experience. This intervention aligns with recognized implementation science frameworks, while addressing aspects pertinent in low- and middle-income countries.

A risk nomogram for 30-day mortality in Chinese patients with acute pancreatitis using LASSO-logistic regression

Gender differences in the association between weight-adjusted waist index and migraine: A cross-sectional study

Objective This study examines how weight-adjusted waist index (WWI) correlates with the occurrence of migraine in U.S. adults. Background Being overweight significantly increases the likelihood of experiencing migraines; nonetheless, conventional metrics like waist circumference (WC) and body mass index (BMI) might not completely capture the level of migraine risk tied to obesity. WWI integrates the strengths of WC while minimizing its correlation with BMI, which might make it a more accurate indicator of central obesity-related migraine susceptibility. Methods This study performed a cross-sectional analysis using data from 9,688 participants obtained from the National Health and Nutrition Examination Survey (NHANES), covering the years 1999–2004. Migraine occurrence was evaluated through questionnaires, and participants’ WWI was computed. Weighted multivariable logistic regression models were used to examine the association between WWI and migraines. Restricted cubic splines (RCS) were applied to evaluate the dose-response relationship between WWI and migraines. Furthermore, interaction tests and subgroup analyses were executed. The receiver operating characteristic (ROC) curve, paired with DeLong et al.’s test, was employed to compare the predictive power of WWI, BMI, and WC for migraines. Results The overall prevalence of migraines was found to be 21.50% (weighted population: 31,888,075 out of 148,278,824). In Model 3, the link between WWI and migraines in women showed no statistical significance (OR = 0.94, 95% CI: 0.82–1.07). In this model, each unit increase in WWI among men was linked to a 22% higher risk of migraines (OR = 1.22, 95% CI: 1.05–1.42). When stratified by quintiles, individuals in the third quintile (Q3) displayed a 69% higher likelihood of experiencing migraines compared to those in the first quintile (Q1) (OR = 1.69, 95% CI: 1.19–2.40), with a significant inflection point observed at 10.95 cm/√kg. Significant interactions were noted among various age groups (p for interaction = 0.018). WWI demonstrated a stronger predictive capability for migraine compared to BMI and WC. Conclusion A U-shaped positive correlation of WWI with migraines was observerd among adult males in the U.S., while no significant correlation was found in females. Within the context of BMI and WC, WWI exhibited a superior predictive capacity for migraines.

Typing of clinical and reference strains of Saccharomyces cerevisiae using pulsed-field gel electrophoresis and MALDI-TOF MS

Can laboratory-based XAFS compete with XRD and Mössbauer spectroscopy as a tool for quantitative species analysis? Critical evaluation using the example of a natural iron ore

While X-ray diffraction (XRD) is a commonly used method for quantification analysis using Rietveld refinement and quantitative Mössbauer spectroscopy is sporadically used primarily for iron speciation, laboratory X-ray Absorption Fine Structure Spectroscopy (lab-XAFS) is rarely applied for the quantitative determination of sample compositions. With the recent developments of laboratory-based XAFS spectrometers, this method becomes more interesting for many applications as well as for quantification. The goal of this study is to compare quantitative lab-XAFS via Linear Combination Fitting (LCF) of reference spectra with XRD and Mössbauer spectroscopy. Iron species analysis with the focus on the determination of the mass ratio alpha-iron(III) oxide (α-Fe2O3)/iron(II, III) oxide (Fe3O4) was used as an example. The examinations were performed on synthetic α-Fe2O3/Fe3O4 model mixtures and, predominantly, on a natural iron ore sample mainly consisting of the minerals hematite and magnetite, thus, these two iron oxides. For the iron K-edge lab-XAFS measurements an X-ray tube-based spectrometer using the von Hamos geometry with Highly Annealed Pyrolytic Graphite (HAPG) mosaic crystal optic was used. The capabilities and challenges of each method are discussed. The quantitative model mixtures examinations by lab-XAFS show results and accuracies similar to those obtained by XRD and Mössbauer spectroscopy. However, while the quantitative results for the iron ore investigations by lab-XAFS are in good agreement (deviation of 2 percent points) with the XRD results, the composition determined by Mössbauer spectroscopy differs clearly from the lab-XAFS and XRD results. Furthermore, the Mössbauer spectroscopic examinations hint the presence of an additional iron oxide species affecting the quantification. Besides the still common challenges in identification, differentiation and quantification of different iron oxides, the results show that quantitative lab-XAFS can particularly compete with quantitative XRD when determining the species composition of one element. This makes lab-XAFS particularly well-suited for routine analytics.

Courtship and spawning behaviour of medaka in a semi-outdoor environment initiating at midnight

Abstract Reproductive timing is a critical ecological trait that directly influences fitness. Medaka (Oryzias latipes), a small freshwater fish, is widely used as a model organism in various scientific fields. However, ecological studies conducted under (semi-) natural conditions remain limited. Although, spawning has been reported to occur within 1 h before and after sunrise, direct observations remain scarce. We investigated the timing of spawning initiation and associated courtship in medaka through 24-h observations using infrared cameras under semi-natural conditions. During the experiments, sunrise occurred at approximately 4:45. Observations of the 31 pairs revealed that spawning occurred between 1:05–9:48, with a peak at 2:00–4:00. Unlike previous reports but like the most recent fieldwork, only 26% of the total spawning events (8/31) were observed within 1 h before and after sunrise. Male courtship behaviours, including following females and quick circle displays, increased from midnight, peaking between 2:00–5:00. This study provides new insights into the natural reproductive timing of medaka, suggesting a possible adaptation to nocturnal spawning, likely as a strategy to reduce predation on both parents and eggs. It also underscores the importance of investigating the ecology of model organisms under (semi-)natural conditions to gain a more comprehensive understanding of biological phenomena observed in laboratory settings.

Verity plots: A novel method of visualizing reliability assessments of artificial intelligence methods in quantitative cardiovascular magnetic resonance

Background Artificial intelligence (AI) methods have established themselves in cardiovascular magnetic resonance (CMR) as automated quantification tools for ventricular volumes, function, and myocardial tissue characterization. Quality assurance approaches focus on measuring and controlling AI-expert differences but there is a need for tools that better communicate reliability and agreement. This study introduces the Verity plot, a novel statistical visualization that communicates the reliability of quantitative parameters (QP) with clear agreement criteria and descriptive statistics. Methods Tolerance ranges for the acceptability of the bias and variance of AI-expert differences were derived from intra- and interreader evaluations. AI-expert agreement was defined by bias confidence and variance tolerance intervals being within bias and variance tolerance ranges. A reliability plot was designed to communicate this statistical test for agreement. Verity plots merge reliability plots with density and a scatter plot to illustrate AI-expert differences. Their utility was compared against Correlation, Box and Bland-Altman plots. Results Bias and variance tolerance ranges were established for volume, function, and myocardial tissue characterization QPs. Verity plots provided insights into statstistcal properties, outlier detection, and parametric test assumptions, outperforming Correlation, Box and Bland-Altman plots. Additionally, they offered a framework for determining the acceptability of AI-expert bias and variance. Conclusion Verity plots offer markers for bias, variance, trends and outliers, in addition to deciding AI quantification acceptability. The plots were successfully applied to various AI methods in CMR and decisively communicated AI-expert agreement.

Pitch biases sensorimotor synchronization to auditory rhythms

Initial validity and reliability testing of the SGBA-5

Background A growing body of research indicates that sex (biological) and gender (sociocultural) influence health through a variety of distinct mechanisms. Sex- and Gender-Based Analysis (SGBA) techniques could examine these influences, however, there is a lack of nuanced and easily implementable measurement tools for health research. To address this gap, we created the Sex- and Gender-Based Analysis Tool – 5 item (SGBA-5). Objectives This research aims to assess the validity and reliability of the SGBA-5 for use in health sciences research where sex or gender are not primary variables of interest. Methods A Delphi consensus study was conducted with Canadian researchers (n = 14). The Delphi experts rated the validity of each SGBA-5 item on a 5-point Likert scale each round, receiving summary statistics of other experts’ responses after the first round. A conservative threshold for consensus agreement (75% rating an item 4+ of 5) was used given the novelty of this scale’s items. Reliability was assessed through a two-armed test-retest study. The university student arm (n = 89) was conducted in-person (on paper), and the older adult arm (n = 71) was conducted online (digitally). Results The Delphi study ended after three rounds; experts reached consensus agreement on the validity of the biological sex item of the SGBA-5 (93%) and consensus non-agreement on each of the gendered aspect of health items (identity: 64%, expression: 64%, roles: 50%, relations: 57%). Both the student arm (sex item: κ=1.00,95%CI(1.00,1.00), gendered items: ICC(A,1)≥.899,95%CI(.851,.933)) and the older adult arm (sex item: κ=1.00,95%CI(1.00,1.00), gendered items: ICC(A,1)≥.865,95%CI(.772,.920)) of the test-retest study indicated that all items were reliable. Conclusions The novel SGBA-5 tool demonstrated reliability across all scale items and validity of the biological sex item. The gendered aspects of health items may be valid. Future research can further develop the SGBA-5 as a tool for use in health research.

Analyzing metaverse-based digital therapies, their effectiveness, and potential risks in mental healthcare

Heterogeneity of diagnosis and documentation of post-COVID conditions in primary care: A machine learning analysis

Background Post-COVID conditions (PCC) have proven difficult to diagnose. In this retrospective observational study, we aimed to characterize the level of variation in PCC diagnoses observed across clinicians from a number of methodological angles and to determine whether natural language classifiers trained on clinical notes can reconcile differences in diagnostic definitions. Methods We used data from 519 primary care clinics around the United States who were in the American Family Cohort registry between October 1, 2021 (when the ICD-10 code for PCC was activated) and November 1, 2023. There were 6,116 patients with a diagnostic code for PCC (U09.9), and 5,020 with diagnostic codes for both PCC and COVID-19. We explored these data using 4 different outcomes: 1) Time between COVID-19 and PCC diagnostic codes; 2) Count of patients with PCC diagnostic codes per clinician; 3) Patient-specific probability of PCC diagnostic code based on patient and clinician characteristics; and 4) Performance of a natural language classifier trained on notes from 5,000 patients annotated by two physicians to indicate probable PCC. Results Of patients with diagnostic codes for PCC and COVID-19, 61.3% were diagnosed with PCC less than 12 weeks after initial recorded COVID-19. Clinicians in the top 1% of diagnostic propensity accounted for more than a third of all PCC diagnoses (35.8%). Comparing LASSO logistic regressions predicting documentation of PCC diagnosis, a log-likelihood test showed significantly better fit when clinician and practice site indicators were included (p < 0.0001). Inter-rater agreement between physician annotators on PCC diagnosis was moderate (Cohen’s kappa: 0.60), and performance of the natural language classifiers was marginal (best AUC: 0.724, 95% credible interval: 0.555–0.878). Conclusion We found evidence of substantial disagreement between clinicians on diagnostic criteria for PCC. The variation in diagnostic rates across clinicians points to the possibilities of under- and over-diagnosis for patients.

A comparative study on trajectory tracking control methods for automated vehicles

Knowledge, attitudes, and practices of cardiac rehabilitation and barriers to referral among cardiologists in Saudi Arabia: A cross-sectional survey

Background Cardiac rehabilitation (CR) is an effective secondary prevention intervention, yet it is globally underutilized. Physicians play a key role in CR uptake by eligible patients through encouragement and referral to the program. This study assessed the knowledge, attitudes, and practices concerning CR among cardiologists in the Kingdom of Saudi Arabia (KSA), identified barriers to patient referrals to CR programs, and proposed strategies to increase service adoption. Methods We conducted an observational cross-sectional study in which an online questionnaire was distributed via email to cardiologists and cardiology fellows during the Saudi Heart Association’s annual conference in October 2023 and through social media platforms. Participants were required to have at least six months of clinical practice in managing patients, including those with coronary heart disease (CHD) following percutaneous coronary intervention (PCI). Results Of the 140 cardiologists surveyed, 106 completed more than 95% of the questionnaires. The cohort, which was primarily male (88.7%), included 67% consulting cardiologists, 15.1% fellows, and 17.9% specialists in areas such as general cardiology (29.2%), interventional cardiology (21.7%), and echocardiography (20.8%). Major barriers included a lack of local CR services (72.6%) and inadequate referral systems (41.5%). Despite the challenges and mixed views on the effectiveness of CR in KSA, attitudes toward CR were largely positive. The knowledge scores averaged 7.97, indicating a moderate to high understanding of CR services and benefits. Referral practices vary widely and are influenced by demographic and workplace factors, mainly geographic location. Conclusions While cardiologists in KSA generally have reasonable knowledge of CR and its benefits, substantial barriers hinder its broader implementation. There is enthusiasm for adopting diverse CR models; thus, further research is necessary to explore and evaluate alternative CR approaches, including home-based CR and telerehabilitation, to enhance patient care.

Liquefaction characteristics of desaturated coral sand foundation with upper building

Modeling the spectrum and determinants of multimorbidity risk among older adults in India

Background India is passing through a parallel phase of demographic and epidemiological transition coupled with the shifting burden of multimorbidity. Unhealthy ageing and escalating morbidity burden have been identified as key drivers of this shifting multimorbidity risk among older adults in India. This study aims to assess the distribution of morbidities and multimorbidity, provide new estimates of multimorbidity risk by socio-economic and demographic factors and further evaluate the multimorbidity count risk conditioned on leading factors. Methods This study used the nationally representative Longitudinal Ageing Study in India (LASI), Wave – 1, 2017–18, data of individuals aged 45 years and above. First, we assessed the relative proportional share of morbidities and compositions of multimorbidity counts over age. Second, we applied the Random Forest (RF) model to estimate the age-specific risk of multimorbidity susceptibility associated with socio-economic and demographic factors over age. Finally, conditional plots were constructed to assess the distributional composition of the leading factors affecting multimorbidity counts. Results The prevalence of multimorbidity was 43.20%. Eye disorders, followed by cardiovascular disease (CVDs), had the highest proportional share over age. Endocrine diseases, Gastrointestinal Conditions, and Infectious diseases showed a concordant decreasing proportional share in later age. The relative share of five or more multimorbidity counts increased significantly with age. The median expected risk of multimorbidity was significantly higher in females (66 years) than in males (71 years). The study also provides empirical evidence that individuals with higher levels of education, obesity, currently working, and poor childhood health were more prone to higher risk of multimorbidity at an early age. Furthermore, obesity was significantly associated with early multimorbidity onset and led to a pronounced escalation of complex multimorbidity progression, particularly in females. Conclusions Collective public health interventions are crucial to address early multimorbidity onset and burden disparities, to promote healthier ageing, and to address etiological factors.

Bioinformatics analysis of comorbid mechanisms between ischemic stroke and end stage renal disease

Seroprevalence of hepatitis A virus infection in urban and rural areas in Vietnam

Background/objectives The prevalence of hepatitis A virus (HAV) is associated with socioeconomic conditions, access to clean drinking water, and improvements in sanitation. In Vietnam, epidemiological data on HAV have been limited over the past two decades. This study aims to assess age-specific HAV seroprevalence across two distinct geographic regions, urban and rural areas, and identify the risk factors associated with HAV seropositivity in Vietnam. Methods This cross-sectional seroprevalence study was conducted in two distinct areas in Vietnam. Serological testing for anti-HAV total antibodies was performed, and socio-demographic questionnaires were administered to all participants. The age at the midpoint of population immunity (AMPI) was calculated and analyzed. Results A total of 1,281 participants aged 1–80 years were included, with 649 from urban areas and 632 from rural areas. Of the total participants, 33.2% were aged <15 years. Overall, HAV seropositivity was 69.2%, with urban areas exhibiting significantly lower seropositivity (57.9%) compared to rural areas (80.7%) (p < 0.001). The AMPI was 29 years, indicating Vietnam is at intermediate HAV endemicity. Multivariate analysis identified key risk factors for HAV infection, including age and rural residence. Conversely, participants with higher educational levels and those who consumed boiled drinking water were less likely to be HAV seropositive. Conclusions The study identified significant differences in the HAV seroprevalence between urban and rural areas, providing critical data for public health officials. These findings highlight the key role of targeted public health interventions and vaccination programs in mitigating HAV infection rates and reducing the disease burden, particularly among high-risk populations in Vietnam.