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Optimized dicentric chromosome dose–response curves with centromere probes improve low-dose radiation biodosimetry

U.S. trends of anti-vascular endothelial growth factor use from 2017–2023: An analysis of medicare, medicaid, and commercial insurance

Purpose Anti-vascular endothelial growth factor medications are a cornerstone in the treatment of many macular diseases in modern ophthalmology. These medications accrue significant economic burdens to individuals and health systems, and recent data on health-system level practice patterns involving agent selection is lacking. We sought to examine utilization of intravitreal anti–VEGF agents from 2017 to 2023 across various payors and diagnoses in the United States in order to analyze trends in usage. Methods A retrospective cross-sectional study was performed . Data were obtained from the Epic Cosmos database, comprised of de-identified data from the electronic health record, Epic, of 238 million patients from all 50 states from January 1, 2017 to December 31, 2023. Encounters where a patient received an intravitreal injection in an ophthalmology clinic were categorized by intravitreal medication ordered, visit diagnosis, and primary insurance payor. The overall usage rates of each medication across different diagnoses and primary payor were compared. Total number of injections per year of anti-VEGF medication, the rate per 100000 ophthalmology encounters (OE), and the rate in different retinal conditions and with various insurance providers were the main outcome measures. Results From 2017–2023, there were 571,545 anti-VEGF injections administered, with 53.6% aflibercept 2 mg (306,247/571,545; 625.8/000 OE), 34.8% bevacizumab 1.25 mg (198,696/571,545; 414.7/100000 OE), 7.83% ranibizumab 0.3 mg and 0.5 mg (44,803/571,545; 99.2/100000 OE), and 3.43% faricimab 6 mg (19,624/571,545; 32.8/100000 OE). Brolucizumab 6 mg, ranibizumab-eqrn 0.5 mg, ranibizumab-nuna 0.5 mg, and aflibercept 8 mg accounted for <1% of all injections. From 2017–2023, the rate of aflibercept 2 mg increased from 361.3 injections/100000 OE to 913.1, bevacizumab increased from 274.1 to 538.1, and ranibizumab decreased from 92.4 to 64.0. The rate of faricimab increased from 37.9/100000 OE to 189.9 from 2022–2023. Patients with Medicare received aflibercept 2 mg at higher rates than bevacizumab (364.3/100000 OE vs 187.1, respectively) [t(6) = 5.67, p = 0.001] and faricimab (19.4/100000 OE), a pattern not seen in commercially insured [t(6)=2.07, p > 0.05] patients. Medicaid patients had a marginally significant difference in use of bevacizumab (M = 19.9/100000 OE, SD = 7.32) and aflibercept 2 mg (16.1/100000 OE, SD = 7.22) [t(6)]=2.95, p = 0.026]. Conclusions Aflibercept 2 mg was the most common drug used overall from 2017–2023. Faricimab had the highest absolute and relative increase in utilization from 2022–2023. Patients with Medicare B or C were significantly more likely to receive aflibercept over bevacizumab.

Five-factor model-based personality profiles in South Korea

Symptomatic chikungunya and chronic post-infection arthralgia in a highly endemic setting in Northeastern Brazil, 2018–2019: Clinical characteristics, prevalence and associated factors

Chikungunya, an Aedes -borne disease, poses a significant global health threat due to its substantial morbidity. The prevalence of symptomatic chikungunya virus (CHIKV) infection and chronic arthralgia, as well as their associated factors, vary geographically and across studies. We estimated the prevalence of these outcomes in a household-based survey conducted in a large northeastern Brazilian city (2018–2019) approximately three years after the city’s first CHIKV outbreak (2016). Sociodemographic and clinical data were collected through interviews, and arboviruses serostatus (IgG and/or IgM) was determined using ELISA. Arthralgia severity was assessed via Visual Analog Scale (VAS). Prevalence estimates (95% CI) and adjusted prevalence ratios (aPRs) were estimated using Poisson regression with robust variance. Principal Component Analysis (PCA) was used to address multicollinearity and identify latent risk profiles . Of the 760 CHIKV-exposed participants, 70% (95% CI: 66.7–73.2; n = 532) reported symptomatic infections. Among those reporting arthralgia (n = 499), 36.5% (95% CI: 32.4–40.8) experienced symptoms lasting >90 days, and of these, over 70% reported severe pain (VAS ≥ 8). In multivariable analyses, older age (aPR = 1.21 [36–50 years], aPR = 1.19 [51–65 years]), female sex (aPR = 1.19; 95% CI: 1.08–1.32), and prior DENV exposure (aPR = 1.45; 95% CI: 1.03–2.04) were associated with – symptomatic infection, whereas higher income showed a protective association. PCA confirmed these formed distinct risk profiles; a sociodemographic component (older age, prior DENV and single marital status) and a biological sex component each independently increased the odds of symptomatic disease by 31% (aOR=1.31). For chronic arthralgia, risk increased with older age (aPR = 4.60 [51–65 years]), female sex (aPR = 1.70; 95% CI: 1.29–2.25), and severe acute pain (aPR = 2.91; 95% CI: 1.86–4.55), but inversely associated with low income (aPR = 0.67). These findings underscore the need for targeted interventions, particularly for older adults, women, and low-income groups. Further studies are needed to elucidate the immunological mechanisms underlying these associations.

Retraction Note: Restoring the Taxol biosynthetic machinery of Aspergillus terreus by Podocarpus gracilior Pilger microbiome, with retrieving the ribosome biogenesis proteins of WD40 superfamily

Estimating actual striking forces using attenuation properties of Taekwondo protectors

Background: Protectors significantly attenuate impact forces, yet their quantitative characteristics remain poorly understood. While accurately measuring actual striking force is essential for performance evaluation, practical and safety challenges prevent direct measurement on athletes. The protector’s attenuation obscures the true impact, necessitating a method to estimate the original force from the attenuated data. Methods: A controllable pendulum-based impact testing apparatus was developed to evaluate force attenuation characteristics of Taekwondo body protectors. The system delivered repeatable impacts across varying magnitudes and contact durations to a mannequin equipped with a protector. Simultaneous measurements of input and transmitted forces through the protector enabled quantification of attenuation ratios under controlled conditions. To demonstrate practical application, five Taekwondo athletes performed standardized kicks on the instrumented protector setup, allowing estimation of their actual striking forces using the derived attenuation factor. Results: Force attenuation ratios demonstrated high consistency across impact magnitudes ranging from 300 to 5800 Newtons, with impact duration variations showing minimal influence on attenuation performance. Linear attenuation relationships were established between input and transmitted forces ( R 2 ≥ 0.987 ), enabling derivation of a predictive attenuation factor. Validation testing with the pendulum system showed that the estimated input force trajectories achieved an nRMSE of 3.5%. Averaged across the entire force range, the MAPE was 4.7% for maximum force, 1.4% for impact duration, and 3.5% for impulse. Applying the attenuation factor to standardized kicks performed by five Taekwondo athletes yielded estimated maximum striking forces ranging from approximately 1300 to 1800 Newtons. Conclusion: This study establishes the first quantitative characterization of impact attenuation in Taekwondo body protectors, providing a validated attenuation factor for estimating striking forces from transmitted forces. These findings demonstrate a practical methodology for quantifying striking forces that are otherwise difficult to measure.

Assessment and treatment of metabolic acidosis in CKD: a registry-based study

A TGFB2/TNF-induced in vitro model of proliferative vitreoretinopathy (PVR) using ARPE-19 cells confirms nicotinamide as an inhibitor of EMT and VEGFA secretion

Proliferative vitreoretinopathy (PVR) is a vision-threatening fibrotic retinal disorder characterized by the epithelial-mesenchymal transition (EMT) of retinal pigment epithelial (RPE) cells. In this study, we established a pathophysiologically relevant in vitro model by co-stimulating ARPE-19 cells with transforming growth factor beta 2 (TGFB2) and tumor necrosis factor-alpha (TNF), referred to as ‘TNT’, and evaluated the anti-fibrotic and anti-angiogenic effects of Nicotinamide (NAM), a vitamin B3 derivative previously reported to counteract fibrosis in various disease models. Confluent ARPE-19 cells were treated with TGFB2, TNF, or TNT for up to six days. EMT progression was assessed via immunocytochemistry, Western blotting, and collagen gel contraction assays. Live-cell imaging (LCI) combined with Hoechst 33342 nuclear staining and automated tracking using Fiji/TrackMate enabled real-time analysis of cell migration and multicellular aggregation. VEGFA secretion was quantified by ELISA. TNT stimulation induced synergistic EMT-like features, including cell elongation, directional migration, extracellular matrix (ECM) remodeling, gel contraction, and formation of multicellular aggregates. TrackMate-based analysis revealed coordinated nuclear migration under TNT conditions. VEGFA secretion was significantly elevated at early time points. NAM co-treatment reduced ECM protein expression (FN1, COL1A1), attenuated migration and contraction, and significantly lowered VEGFA release. This TNT-based ARPE-19 model represents a robust, live-cell-compatible in vitro system that mimics both fibrotic and pro-angiogenic aspects of PVR. It allows real-time assessment of EMT progression and is suitable for screening anti-fibrotic compounds. Our findings suggest that Nicotinamide mitigates both fibrotic and angiogenic responses in this model and may hold therapeutic potential for fibrotic retinal diseases.

Perivascular pathology, not macrovascular complexity, governs glymphatic-related dysfunction in preclinical cerebral small vessel disease

Drug price dynamics following changes in procurement method in the public healthcare setting in Malaysia

Pooled and segmented procurement are common in public health, but changing needs may prompt method shifts. Understanding their impact on drug prices is crucial for informed policy decisions. This study aimed to evaluate the impact of procurement method changes from pooled to segmented (P → S) and from segmented to pooled (S → P) on drug prices within Malaysia’s public health sector. A five-year retrospective analysis was conducted using data from eight therapeutic subgroups, covering 73 drugs and 151 comparative procurements. The product price index measured price changes between procurement groups, and differences in probabilities and price index were assessed using Pearson Chi-square and Mann-Whitney U tests. The significance level was p < 0.05. Out of 151 comparative procurements, 48.34% (n = 73) were P → S, and 51.66% (n = 78) were S → P. Significant differences were found in all pairwise comparisons between the groups for changes in drug prices. Specifically, the proportion of procurements with price decreases was significantly higher in the S → P group (79.49%) than in the P → S group (30.14%) (p < 0.0005), while price increases were more frequent in the P → S group (50.68% vs. 15.38%, p < 0.0005). Price stability was also more commonly observed in the P → S group (19.18%) than in the S → P group (5.13%) (p = 0.008). Overall, the P → S group had statistically significant higher mean ranks of 101.08 than the S → P group (mean rank = 52.53) with U = 151, z = −6.824, p < 0.0005, indicating that the S → P group tended to have lower prices on average than the P → S group. Pooled procurement potentially saves costs over segmented methods, but understanding both options’ pros and cons is crucial for tailored solutions.

Boosting tribo-mechanical, thermal expansion and electrical performance of waste polytetrafluoroethylene using high-strength carbide ceramics

Abstract Polytetrafluoroethylene (PTFE) is widely used across various industrial and technological fields, including aerospace, automotive, electronics, and chemical processing. This work presents a sustainable approach to reusing PTFE waste and enhancing the limited applications of PTFE, which are constrained by its inferior mechanical properties, thermal expansion, and wear resistance. The reuse of PTFE scrap produced by lathe shops improves its previously mentioned properties by adding high-strength and high-stability ceramics. In this context, powder metallurgy technology produces PTFE-based composites reinforced with boron carbide (B 4 C) nanoparticles and graphene nanosheets. The phase composition and microstructure were determined using X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM) techniques. XRD indicated the presence of PTFE and B 4 C phases in the chart of the specimens and the absence of graphene nanosheets due to their small quantity. The hybrid composite PTFE/5vol.% B 4 C/1 vol% graphene (GB6) recorded an increase in the microhardness, compressive stress, and Young’s modulus of 138.55%, 114.86%, and 78.70%, respectively, relative to the PTFE matrix (GB0). The results also indicated that the addition of reinforcements led to a significant improvement in wear resistance and thermal stability, with the GB6 sample recording a decrease in wear rate, coefficient of friction, and thermal expansion coefficient (CTE) value of 40.73%, 42.49%, and 57.94%, respectively, compared to the CB0 sample. Moreover, the addition of reinforcements to the PTFE matrix has the positive effect of increasing the electrical conductivity.

RUL prediction method based on sequential health index evaluation with multidimensional coupled degradation data

Remaining Useful Life (RUL) prediction is crucial for implementing predictive maintenance strategies, however, RUL prediction is severely constrained by the lack of high-quality labeled life-cycle data. Moreover, complex coupling relationships exist within the obtained multidimensional degradation data, making it difficult to construct an accurate health index (HI) for the system. To address this challenge, we propose an RUL prediction method based on sequential healthy index evaluation which incorporate two parts: the parameter prediction process and the health index fusion process. The core innovation of this study is an RUL prediction method that integrates a CNN-Transformer hybrid model with a sequential health index evaluation scheme. Compared to traditional data-driven methods, our approach incorporates a chunk-interaction mechanism into the multi-head attention design, thereby reducing model complexity and computational demands. Simultaneously, the sequential evaluation scheme dynamically constructs the health index based on the Mahalanobis distance and the Sequential Evaluation Ratio (SER), which eliminates the reliance on high-quality labeled life-cycle data. Experimental results demonstrate that the proposed method outperforms existing deep learning approaches (such as LSTM, Transformer, and Att-BiGRU) across multiple datasets, exhibiting higher prediction accuracy and robustness, particularly in label-scarce scenarios.

Immunoinformatics-based design and evaluation of a multi-epitope vaccine against Vibrio fluvialis

Research on missing value prediction of measured ERT data for coal mine based on a GRNN algorithm

In the process of long-term monitoring of the coal seam floor of a coal mining face using electrical resistivity tomography (ERT), the data loss caused by electrode disconnection adversely affects early warning of water inrush and prevents the identification of hidden dangers, hindering safe production. Due to the particularity of the monitored environment, the maintenance of offline electrodes may not be timely. Therefore, how to deal with the loss of measured data caused by electrode disconnection has become a problem that must be solved in the long-term monitoring process. In this paper, we analyze the effect of electrode disconnection on the measured data. Then, the principle of the general regression neural network (GRNN) algorithm is introduced. The missing values in the measured data are predicted using the GRNN algorithm. The results of verification experiments conducted in a water tank show that when the original data integrity is 82.96%, the predicted data accuracy reaches 91.46%, and when the original data integrity is only 55.56%, the predicted data accuracy still reaches 82.45%. Finally, actual applications of the proposed method are carried out on coal mining faces. A set of data with an integrity of 73.8% is predicted. Compared with the measured data when all the electrodes are online, the accuracy of the predicted data is 85.18%. The accuracy of the data predicted using the proposed method is 14.99% higher than that of the data predicted using the commonly used mean value interpolation method.

Nomogram-based analysis of plasma albumin and C-reactive protein 30 days before bloodstream infection for 30-day mortality in Singapore and Denmark

Linking culture and individual behavior: The concept and measurement of cultural consonance

Culture has been a central concept in the social sciences for well over a century. Yet, a theory of culture with an associated measurement model providing the means to systematically study its effects has proven elusive. Developments in cognitive culture theory over the past several years provide a new perspective and a new set of tools. Culture can be conceptualized as a set of shared cognitive models that encode the information required for individuals to function in a given social setting. These cultural models can be elicited and examined in detail using the methods of cultural domain analysis, and the cultural consensus model (CCM) can be used to test for sharing and to describe variation in culture. Using the results of cultural consensus analysis as a foundation, cultural consonance can be measured for individuals. Cultural consonance is the degree to which individuals, in their own behaviors, approximate the prototypes for behavior encoded in cultural models. Cultural consonance thus extends cognitive culture theory to an examination of culture expressed in behavior. In this article, this theoretical and methodological orientation is presented, and some implications of its empirical examination are discussed.

Using GDACS to anticipate clinical and operational burden after earthquakes: A global event-level analysis (2020–2024)

Global Disaster Alert and Coordination System (GDACS) alerts are widely used after earthquakes, yet their clinical relevance is uncertain. We performed a retrospective, global, event-level study spanning 2020–2024. To avoid double counting, alerts were clustered into country-bounded representatives using a 48-hour gap, retaining the alert with the highest GDACS score (n = 85; Red = 17, Orange = 68). Primary outcomes were reported deaths and field-hospital deployment. Associations used Spearman correlation; deployment was modeled with Firth logistic regression. Sensitivity analyses used alternative deployment definitions and composite windows. The GDACS score correlated with deaths (ρ = 0.522, p = 3.0 × 10 ⁻ ⁷). Field-hospital deployment occurred in 52.9% of Red events and 0% of Orange events. The GDACS score strongly predicted deployment (OR=42.7, 95% CI 4.7–385.7), with AUC = 0.98 and Brier = 0.034. An exploratory exposure-normalized subset where GDACS reported population “within 100 km” (n = 19) showed directionally consistent results (ρ = 0.50, p = 0.029).GDACS metrics provide early, scalable indicators for surge planning, but are hazard- and exposure-centric and cannot capture mediators such as collapse dynamics or health-system resilience. Treating GDACS as a first-layer signal, complemented by subnational exposure and rapid damage assessment, can support more timely, evidence-based medical response after major earthquakes.

The relationship between emotional intelligence and work performance among palestinians’ midwives in obstetrics and gynecology departments

Barriers and facilitators of tuberculosis treatment adherence among nomadic populations in Sub-Saharan Africa: A scoping review protocol

Introduction Tuberculosis (TB) is a notable public health issue in sub-Saharan Africa (SSA), disproportionately affecting vulnerable populations such as nomads. Their migratory lifestyles limit consistent access to TB diagnostic and treatment services, leading to delays in diagnosis and challenges in completing the full TB treatment regimen. This scoping review aims to map the existing evidence on barriers and facilitators of TB treatment adherence among nomadic populations in SSA. Methods The review will follow the Arksey and O’Malley methodological framework. Relevant published literature will be searched using a combination of keywords, Boolean terms, and Medical Subject Headings (MESH) across PubMed, Scopus, Google Scholar, and relevant grey literature sources. Eligible publications will include empirical research examining the barriers and facilitators that influence tuberculosis (TB) treatment adherence among nomadic populations. Study selection and data extraction will be undertaken independently by two reviewers, with discrepancies adjudicated by a third reviewer. The findings will be synthesized narratively in alignment with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Review (PRISMA-ScR) guidelines. Conclusion This review seeks to map the existing evidence on the barriers and facilitators shaping TB treatment adherence among nomadic populations in sub-Saharan Africa. It is anticipated that this analysis will provide a foundation for a more targeted inquiry, support the development of context-appropriate TB strategies and guide policymakers in designing interventions better aligned with the needs of highly mobile populations. Trial registration PROSPERO registration number CRD420250651525

Comparative analysis of sex-based, vendor-based, and species differences in cytochrome P450 metabolism

Abstract Hepatic clearance is crucial as it directly impacts drug exposure, efficacy, and safety. Cytochrome P450 (CYP450) enzymes play a pivotal role in drug metabolism and exhibit differences based on sex, species, and commercial liver microsome vendors. These variables can directly influence translational accuracy when preclinical data are applied to human drug development. In this study, we evaluated metabolic stability of isozyme-selective compounds across human, rat, and mouse liver microsomes, incorporating both male and female microsomes and multiple vendors. Our analysis revealed three layers of variability: (1) sex-specific differences consistent with prior clinical observations, where certain substrates displayed markedly faster clearance in one sex; (2) interspecies divergence, such as male-predominant isoforms in rodents without direct human orthologs; and (3) vendor-related discrepancies, where the same species-sex pool yielded divergent stability outcomes depending on microsome source. Together, these findings illustrate the combined effects of sex, species, and vendor source that contribute to variability in CYP450-mediated metabolism. By systematically comparing these factors, our work underscores the importance of considering these variables during early preclinical studies. Accounting for these sources of variability may improve the translational reliability of in vitro assays, reduce costly late-stage failures, and better support the development of safe and effective therapeutics.