Browse Articles

Understanding motivations of older women to continue or discontinue breast cancer screening

Breast cancer screening guidelines indicate screening in women over 75 years of age is optional, depending upon patient health and preferences. To better understand the preferences and decision-making of older women, their experiences and perceptions concerning screening need to be linked to their intention to continue or discontinue screening. This study used a qualitative comparative analysis to identify the characteristics and themes linked to the intention to continue or discontinue screening. To capture the range of experiences and preferences, a purposive sample of community-residing adults (n = 59) was selected with equal representation of White, Black, and Hispanic women by age (70–74 years and 75 and older) and educational level (≤12 grade and >12 grade). In-depth qualitative interviews explored women’s perceptions of mammograms, the benefits and risks of screening, and personal screening experiences. Interviews were coded and quality-checked by two or more coders. A qualitative comparative analysis (QCA) identified combinations of personal characteristics and themes linked to the intention to continue (n = 32) or discontinue (n = 27) screening. Results indicated personal experiences were strongly linked to the intention to continue or discontinue. Women who mentioned recent screening (within three years) and either a spontaneously mentioned cancer story concerning a friend or family member or a doctor’s screening recommendation intended to continue screening (91% true positive rate, model sensitivity). Women who did not schedule screening and who did not mention a cancer story or a doctor’s recommendation (or neither) intended to discontinue screening (81% true negative rate, model specificity). These experiences transcended differences in race/ethnicity, age, and educational level. Continuation of breast cancer screening in older women is motivated by their personal screening history combined with cancer experiences and/or a doctor’s screening recommendation.

Association of the derived neutrophil-to-lymphocyte ratio with cardiovascular and all-cause mortality

Purpose Accumulating evidence supports the important role of inflammation in disease outcomes. Derived neutrophil-to-lymphocyte ratio (dNLR) is broadly identified as potential prognostic marker in clinical trials or daily clinical practice, but dNLR has never been verified in cardiovascular and all-cause mortality. Methods Overall, 34,392 participants from the National Health and Nutrition Examination Survey (NHANES) were included. The exposure variable was Log-dNLR (dNLR Logarithmic transformation). Participants were categorized according to Log-dNLR quartiles and followed through 31st December 2019. Weighted univariable and multivariable Cox regression were applied to assess the relationship between Log-dNLR evaluated as categorical variables, with cardiovascular and all-cause mortality. Restricted cubic spline (RCS) regression, subgroup analysis, and threshold effect were applied to assess nonlinear relationship between Log-dNLR with cardiovascular and all-cause mortality as well as the effects of special populations. We used multiple sensitivity analyses to reduce selection bias and validate these relationships. Last, the time-dependent weighted receiver operating characteristic (ROC) curve analysis was used to assess predictive accuracy of the Log-dNLR for survival outcomes. Results During a median follow-up duration of 116.90 months, a total of 4,939 all-cause deaths occurred, of which 1,327 were cardiovascular deaths. After adjusting for multiple confounders, compared to the quartile 1, the hazard ratios (HRs) (95% confidence interval, CI) for quartile 4 were 1.38 (95% CI, 1.14–1.68) for cardiovascular mortality and 1.16 (95% CI, 1.06–1.27) for all-cause mortality was identified using RCS regression, with a threshold point of 0.370. Significant differences were observed before and after this threshold point. In addition, there were significant interactions between sex, hypertension status and Log-dNLR (P for interaction = 0.025, 0.005, respectively) for the all-cause mortality risk and significant interactions between age groups, diabetes status and Log-dNLR (P for interaction = 0.007, 0.004, respectively) for the cardiovascular mortality risk. Lastly, ROC analysis revealed that Log-dNLR showed moderate predictive power for all-cause and cardiovascular mortality in the short and long term. Conclusions In summary, elevated dNLR levels are significantly associated with an increased risk of both cardiovascular and all-cause mortality.

Correction: Application of a modified multifunctional short peptide in the treatment of periodontitis

These contact lenses give people infrared vision — even with their eyes shut

Interventions promoting occupational balance in adults: A systematic literature review

Introduction Occupational balance, the subjective perception of satisfaction and balance in engaging in meaningful activities, is fundamental to individuals’ health and well-being. The detrimental impacts of decreased occupational balance are increasingly acknowledged, and interventions are emerging. A comprehensive review of these interventions, targeting occupational balance in adult populations, is needed to ensure effective implementation into both clinical and public health settings. Objective This study aimed to systematically review and synthesize existing interventions that address occupational balance among adults in diverse contexts, and to evaluate their effectiveness. Method A systematic literature search was conducted in PubMed, CINAHL, the Cochrane Library, and EMBASE in April 2024, following the PRISMA guidelines. Peer-reviewed articles published between 2000 and 2024, reporting quantitatively on interventions addressing occupational balance, were included. The NHLBI quality assessment tools were employed to evaluate the risk of bias. A narrative synthesis was performed. Results Of the 347 records identified, 18 publications were included in this review. Study designs comprised randomized controlled trials, observational studies, and pre-post studies. Most participants had specific diagnoses, with a predominance of mental health conditions. The review identified 12 interventions aimed at promoting occupational balance, providing an overview of interventions' target groups, goals, features, and content. Overall effectiveness of identified interventions varied across studies, with six demonstrating statistically significant improvements in occupational balance scores. Clinically meaningful changes were observed in areas such as drug craving, social isolation, and work ability. Conclusion This review identified promising interventions for promoting occupational balance and enhancing health, well-being, and life satisfaction across various settings. Further research should employ controlled experimental designs to evaluate interventions addressing occupational balance across diverse populations, addressing gender and age differences while assessing effectiveness across delivery modes and settings.

Propagation of Laguerre-Gaussian beam intensities through optically thick turbid media

Spin correlations in the nematic quantum disordered state of FeSe

Insulin-self administration among individuals with diabetes: Implications for improved practices

Background Diabetes significantly contributes to both microvascular and macrovascular complications. Effective management depends on meticulous glycemic control, with insulin playing a crucial role. The success of insulin therapy relies on patients’ ability to properly administer insulin and adhere to the administration instructions. Objective This cross-sectional study aimed to evaluate the knowledge and practices of insulin use among patients with type 1 and type 2 diabetes and to identify factors influencing these practices. Methods A validated, self-administered questionnaire was distributed in person to outpatient insulin users with type 1 and type 2 diabetes at King Abdullah University Hospital. In addition to socio-demographics and health characteristics, the questionnaire evaluated patients’ knowledge regarding insulin, its administration, and insulin use practices. Quantile regression was used to explore factors associated with insulin administration practices. Results The study included 402 patients, 53.0% of which are females, with a median age of 54 years. The median (interquartile range) knowledge score was 5 (4–6) out of a maximum possible score of 9, while the median (interquartile range) insulin administration practice score was 80.39 (72.92–85.42) out of a maximum possible score of 100. = . Lower practice levels were associated with older age (coefficient: −0.149, 95%CI: −0.217- −0.082), lack of diabetes information (coefficient: −6.189, 95%CI: −12.041 - −0.337), and reliance on non-scientific information sources (coefficient: −2.409, 95%CI: −4.562 - −0.255). However, higher knowledge scores were associated with better practices (coefficient: 2.516, 95%CI: 1.819–3.213). Conclusions While the study reveals acceptable knowledge and practices regarding insulin self-administration, it also highlights significant gaps that policy initiatives should address by implementing uniform training programs and interventions to promote effective insulin administration practices.

Efficient joint resource allocation using self organized map based Deep Reinforcement Learning for cybertwin enabled 6G networks

Abstract Sixth-generation wireless communication has emerged, stimulating the rapid growth of numerous types of real-time applications that are characterized by their high data computing demands and formation of massive data traffic. Cybertwin-enabled edge computing has become a logical way to satisfy the enormous user demands. However, there are drawbacks to this advancement as well. The effective distribution of resources while balancing the demands for computing, communication, and caching is a major problem in edge networks. The resource allocation problem in dynamic edge computing systems is too complex to address with traditional statistical optimization techniques. Therefore, a Joint Resource allocation method using Self-Organized Map (SOM)-based Deep Reinforcement Learning (DRL) is proposed for cybertwin-enabled 6G wired + wireless (hybrid) networks. This approach controls the clustering capabilities of SOM to organize the state space, followed by the decision-making strength of RL to select optimal actions for resource allocation in dynamic and real-time environments. The objective is to minimize overall latency and energy consumption. From the results analysis, using SOM-DRL, the hybrid network model outperforms the wireless-only model in terms of latency and energy consumption than the existing MATD3 method by achieves 3.34% of energy consumption, 3.17% of latency, and 7.30% of completion time.

CPK28-mediated Ca2+ signaling regulates STOP1 localization and accumulation to facilitate plant aluminum resistance

Assessing the biomedical applicability of biogenically synthesized AuNPs using Salvia splendens extract

This study reports the multifunctional potential of gold nanoparticles (AuNPs) biosynthesized by using Salvia splendens leaf extract (SSLE). The biosynthesized AuNPs were characterized by UV–Visible spectroscopy, transmission electron microscopy (TEM), and dynamic light scattering, followed by the assessment of their anti-cancer, anti-oxidant, anti-inflammatory and anti-bacterial potentials. The biosynthesized SSLE-AuNPs showed a characteristic absorbance peak at 559 nm that corresponds to the surface plasmon resonance (SPR) band of the AuNPs. The zeta potential of SSLE-AuNPs was estimated to be ‒ 21 ± 1.9 mV, and TEM analysis confirmed the particles to be spherical with an average size of 94.8 ± 5.1 nm. The SSLE-AuNPs exhibited dose-dependent antioxidant activity, with IC50 values of 218.5 ± 4.2 µg/mL (DPPH) and 185.3 ± 3.7 µg/mL (ABTS), compared to ascorbic acid (32.1 ± 1.8 µg/mL and 28.6 ± 1.5 µg/mL, respectively. In addition, SSLE-AuNPs exerted potent anti-bacterial effect against Staphylococcus aureus (MIC50 68 ± 2.1 μg/mL) and Klebsiella pneumoniae (MIC50 82 ± 2.3 μg/mL), which was comparable to that of the standard antibacterial agent, tetracycline. Moreover, SSLE-AuNPs induced significant reduction in cellular viability of A549 cells at concentrations of 100, 200 and 400 μg/mL, respectively (p < 0.001). Such cytotoxic potential of SSLE-AuNPs was accompanied by considerable instigation of nuclear fragmentation and condensation, caspase activation, and ROS generation in A549 cells. Furthermore, in vitro studies highlighted the anti-inflammatory potential of SSLE-AuNPs on murine alveolar macrophages (J774A.1) via deflating inflammatory mediators such as the proinflammatory cytokines. To sum up, the present findings have substantiated the antioxidant, antibacterial, anticancer and antiphlogistic properties of SSLE-AuNPs, paving the way for subsequent investigations into green synthesized nano-formulations.

Knowledge, attitude and practice toward probiotics among the general population: a cross-sectional study

Thalamus, evoked responses and triphasic waves

Complexity analysis with chaos control: A discretized ratio-dependent Holling-Tanner predator-prey model with Fear effect in prey population

This study explores a novel two-dimensional discrete-time ratio-dependent Holling-Tanner predator-prey model, incorporating the impact of the Fear effect on the prey population. The study focuses on identifying stationary points and analyzing bifurcations around the positive fixed point, with an emphasis on their biological significance. Our examination of bifurcations at the interior fixed point uncovers a variety of generic bifurcations, including one-parameter bifurcations, period-doubling, and Neimark-Sacker bifurcations. To further understand NS bifurcation, we establish non-degeneracy condition. The system’s bifurcating and fluctuating behavior is managed using Ott—Grebogi—Yorke (OGY) control technique. From an ecological perspective, these findings underscore the substantial role of the Fear effect in shaping predator-prey dynamics. The research is extended to a networked context, where interconnected prey-predator populations demonstrate the influence of coupling strength and network structure on the system’s dynamics. The theoretical results are validated through numerical simulations, which encompass local dynamical classifications, calculations of maximum Lyapunov exponents, phase portrait analyses, and bifurcation diagrams.

Decision making method for operational performance of Chinese commercial banks based on scenario fuzzy sets

Abstract In the original fuzzy set, after optimization, we expanded it into four categories: positive, neutral, negative, and invalid, and applied them to the scenario fuzzy set. This improvement not only fills the gap in the application scope of scenario fuzzy sets in existing literature, but also provides a more comprehensive analytical framework for performance evaluation of commercial banks. Although there have been studies focusing on the classification and application of fuzzy sets, there is still a lack of in-depth exploration on the specific improvement and multidimensional evaluation of situational fuzzy sets. To this end, we propose an improved definition of scenario fuzzy sets and derive the Hamming distance. This distance provides a more comprehensive calculation method when dealing with multi-attribute decision-making problems, enabling decision-makers to more accurately evaluate the relationships between different attributes. By combining the Hamming distance measure and TOPSIS principle, we calculate the optimal value of relative closeness. By comparing the situation fuzzy set with the improved situation fuzzy set, the results show that the improved situation fuzzy set is superior to traditional methods in terms of comprehensiveness and accuracy. This study not only enhances the practical effectiveness of scene fuzzy sets, but also provides a new perspective for subsequent academic research.

Control of epithelial tissue organization by mRNA localization

Abstract mRNA localization to specific subcellular regions is common in mammalian cells but poorly understood in terms of its physiological roles. This study demonstrates the functional importance of Net1 mRNA, which we find prominently localized at the dermal-epidermal junction (DEJ) in stratified squamous epithelia. Net1 mRNA accumulates at DEJ protrusion-like structures that interact with the basement membrane and connect to a mechanosensitive network of microfibrils. Disrupting Net1 mRNA localization in mouse epithelium alters DEJ morphology and keratinocyte-matrix connections, affecting tissue homeostasis. mRNA localization dictates the cortical accumulation of the Net1 protein and its function as a RhoA GTPase exchange factor (GEF). Altered RhoA activity is in turn sufficient to alter the ultrastructure of the DEJ. This study provides a high-resolution in vivo view of mRNA targeting in a physiological context. It further demonstrates how the subcellular localization of a single mRNA can significantly influence mammalian epithelial tissue organization, thus revealing an unappreciated level of post-transcriptional regulation that controls tissue physiology.

Retraction: Activated α2-macroglobulin binding to cell surface GRP78 induces T-loop phosphorylation of Akt1 by PDK1 in association with raptor

Design and numerical analysis of a gap-compensated low loss hollow-core antiresonant fiber with nested elliptical tubes

Bacterial membrane nanovesicles encapsulating prodrug assemblies combine chemical and immunological therapies for chronic bacterial infection

Advancing sentiment analysis for low-resourced african languages using pre-trained language models

While sentiment analysis systems excel in high-resource languages, most African languages facing limited resources, remain under-represented. This gap leaves a significant portion of the world’s population without access to technologies in their native languages. However, multilingual pre-trained language models (PLM) offer a promising approach for sentiment analysis in low-resource languages. Although the absence of large data in African languages poses a challenge for developing PLMs, fine-tuning and task adaptation of existing multilingual PLMs is an alternative solution. This paper explores the use of multilingual PLMs for sentiment analysis in five Southern African languages: Sepedi, Sesotho, Setswana, isiXhosa, and isiZulu. We leverage existing PLMs and fine-tune them for this specific task, avoiding training the models from scratch. Our work expands on the SAfriSenti corpus, a Twitter sentiment dataset for these languages. We employ various annotation techniques to create a labelled dataset and perform benchmark experiments utilising various multilingual PLMs. Our findings demonstrate the effectiveness of multilingual PLM, particularly for closely-related languages (Sotho-Tswana), where the ensemble PLMs method achieved an average weighted F1 score above 63%. In particular, Nguni closely-related languages achieved an even higher average weighted F1 score, exceeding 77%, highlighting the potential of PLMs for sentiment analysis in South African languages.