Browse Articles

Demonstration of a compatibility-based childcare support service using quantum annealing

Sustainable hydrogel from biowaste: Synthesis and characterization of pectin and starch-based hydrogels derived from fruit peel

Arid regions such as the United Arab Emirates face persistent challenges in agricultural productivity due to water scarcity, poor soil quality, and the overuse of chemical fertilizers. As a sustainable alternative, biodegradable hydrogels offer promising solutions owing to their high swelling capacity, water retention ability, and controlled release of water and nutrients. This study explored the synthesis and characterization of eco-friendly hydrogels derived from pectin and starch extracted from orange and banana peels, respectively. These biopolymers are cross-linked using calcium and polyvinyl alcohol, forming hydrogels suitable for agricultural applications. The quality of the extracted biopolymers was assessed by analyzing moisture content, ash content, equivalent weight, solubility, and pectin methylation degree. The results confirmed high purity, with low ash contents of 2.16% (pectin) and 2.31% (starch), and moisture contents of 17.66% and 10%, respectively, indicating good stability and storage potential. The low methoxy pectin content resulted in a degree of methylation of 6.08%, which was favorable for gel formation. Structural and morphological characterization via FTIR, SEM, and SEM-EDX revealed well-defined functional groups, a highly interconnected porous morphology, and structural integrity of the hydrogels even after 20 days of biodegradation. Swelling and pot experiments demonstrated that both hydrogels effectively retained soil moisture for up to 12 days, with swelling ratios ranging from 300% to 350% of their original weight. Biodegradation studies indicated that starch-based hydrogels degraded faster (78.76% weight loss) than pectin-based hydrogels did (67%), likely due to differences in pore size and structural compactness. Overall, the results validate the feasibility of producing sustainable, biodegradable hydrogels from fruit peel waste, with significant potential for water conservation and soil enhancement in arid agricultural systems.

Effectiveness of cleaning methods for clear aligners stained with pediatric iron and multivitamin syrups

Lateral similarity and symmetry of biometric data from the LenStar in a population with cataract

Purpose To investigate the similarity and symmetry of biometric measures between eyes in a large dataset of measurements of both eyes taken with the LenStar optical biometer. Methods Cross-sectional non-randomised study evaluating a dataset containing 13,420 bilateral LenStar 900 biometric measurements on patients without history of eye surgery or ocular pathology taken before cataract surgery, consisting of scalar parameters axial length AL, corneal thickness CCT, anterior chamber depth ACD, lens thickness LT and corneal diameter WTW. The keratometric power vector components equivalent power KEQ were assessed for similarity, and the projections of corneal astigmatism vector KC0 and KC45 were analysed for direct and mirror symmetry with respect to the vertical (sagittal) plane. Results Mean / standard deviation (squared correlation coefficient) difference between right and left eye measures was 0.02 ± 0.31(0.95) / 0.00 ± 0.01(0.93) / 0.00 ± 0.14(0.88) / −0.01 ± 0.22(0.78) / −0.02 ± 0.17(0.87) mm for AL / CCT / ACD / LT / WTW and −0.06 ± 0.48(0.92) dioptres for KEQ. Keratometric astigmatism showed a high degree of mirror symmetry (KC45 of left eyes inverted in sign) which outperforms direct symmetry. The median deviation of the keratometric axes of both eyes considering mirror symmetry was 15 degrees compared to 29 degrees for direct symmetry. Conclusions In most cases, biometric measures match between eyes of a subject, but there are rare situations with large deviations between eyes. Keratometric astigmatism exhibits mirror symmetry. In most cases the biometric measures from the contralateral eye could be used where biometry is unavailable or to double-check before cataract surgery.

Robust prediction and optimization of surface roughness and kerf taper in AWJM of titanium mesh basalt carbon hybrid composites

Lutjanus synagris (Linnaeus 1758) age-based life history using a multi-model inference approach for growth in the southern Gulf of Mexico

Lane snapper Lutjanus synagris is an important species that supports both commercial and recreational fisheries. In the southern Gulf of Mexico, lane snapper is one of the snapper species with the highest annual catch volumes. Nevertheless, information on several life-history traits such as longevity, natural mortality and age at maturity is lacking, which are important for providing appropriate management options. From the total captured lane snapper (n = 1150), 367 were used to estimate the age-life history. Specimens were captured through the small-scale fleet of Yucatan from 2008 to 2009 in southern Gulf of Mexico with total lengths from 14.50–45.90 cm and whole weights from 0.05–1.10 kg. Thin otolith sections were used to determine the age of lane snapper. Left sagittae were embedded in clear epoxy resin, thin sectioned (300 µm thickness), and analyzed using a stereomicroscope, counting opaque zones (white) deposited annually during late spring to early summer. Estimated ages ranged from 0 + to 16 years for females (n = 189) and from 0 + to 15 years for males (n = 164). In the growth modeling process, three candidate models were fitted to improve the plausibility of growth estimates under conditions where both small/young and large/old individuals are poorly represented, and the observed length-at-age data show high variability. A Bayesian approach based on the Markov Chain Monte Carlo was used, with informative priors on the growth parameters. During model fitting, three‑parameter versions were used: k, L ∞ , and a third parameter based on length-at-birth, L 0 ; among these, the last two parameters have the same interpretation across all models. The best growth model by sex was selected based on the Leave-one-out cross-validation technique. The von Bertalanffy growth model was the best-fitting model for growth in both females and males. Growth parameters for females were for maximum mean length or asymptotic length ( L ∞ ) = 32.21 cm total length; growth coefficient ( k 1 ) = 0.27 year -1 ; size-at-age-zero ( L 0 ) = 2.06 cm and for males L ∞ =  28.32 cm total length; k 1  =  0.41 year -1 ; L 0   = 2.03 cm. Natural mortality was estimated at 0.39 year -1 for females and 0.41 year -1 for males. Age at maturity in which 50% of the females and males have reached maturity was A 50  = 3.11 years for females and 1.68 years for males. The reference points of the optimal size (L opt ) and optimal age (A opt ) to harvest the specimens to achieve maximum yield were 26.17 cm total length, 6.20 years for females and 21.24 cm total length, 3.38 years for males. These results on the age-based life history and growth of lane snapper are novel for the southern Gulf of Mexico population. This information forms the basis for developing appropriate management measures, as catch volumes and exploitation levels are steadily increasing.

Development and validation of miner career sustainability scale (MCSS) in intelligent coal mines: a network analysis approach

Expression of Concern: A comparative analysis of microplastic contamination in hermit crab Clibanarius rhabdodactylus Forest, 1953, inhabiting intertidal and subtidal Coastal habitat of Gujarat state

Heat tolerance and thermal safety margins differentially influence the performance of co-occurring mealybug species (Hemiptera: Pseudococcidae) under climate warming

Achieving long-term success in irrigation commons

Which characteristics predict the long-term performance and persistence of irrigation systems? This question has been challenging to answer due to the lack of longitudinal data. Numerous cross-sectional studies have identified a wide range of relevant factors. However, it is unclear which of these factors remain associated with long-term persistence, or what their relative predictive power is. To examine performance and survival after a period of 16–37 years with respect to concerning initial system attributes, we have created a unique longitudinal dataset of 218 community-based irrigation systems in Nepal, separated by three decades. We applied the best available models using several state-of-the-art machine learning algorithms to ensure method independence. Our findings show that farmer-managed systems that receive external support and whose leaders are users perform best. Long-term survival is associated with fair rules, regular member meetings, and occasional external assistance. Good institutional design is consistently among the strongest predictors of long-term performance and persistence in irrigation commons.

YOLO11-based deep learning system for automated tubal patency classification in hysterosalpingography: a comparative study for clinical decision support

Maternal alcohol exposure and atopic dermatitis in offspring: A scoping review protocol

Maternal alcohol use is a modifiable, yet significant public health concern, causing fetal alcohol syndrome and neurodevelopmental disorders. Research has predominantly focused on the neurodevelopmental consequences of maternal alcohol consumption, but growing evidence suggests that these effects may extend to the developing immune system, potentially increasing the risk of allergic and inflammatory conditions such as atopic dermatitis in offspring, which remains underexplored. This scoping review aims to map the available literature on the association between maternal alcohol exposure (preconception and pregnancy) and atopic dermatitis in offspring, including exposure patterns, outcome measures, and hypothesized biological mechanisms. The protocol follows Joanna Briggs Institute methodology with PEO framework (Population: offspring, Exposure: maternal alcohol use, Outcome: atopic dermatitis), and has been registered prospectively on the Open Science Framework (DOI: 10.17605/OSF.IO/EWGPB ). A comprehensive search of electronic databases (PubMed, Scopus, Embase, CINAHL, Web of Science) and grey literature sources will be conducted from inception through the final search date. Two independent reviewers will screen titles, abstracts and full texts, with disagreements resolved by consensus or third-reviewer arbitration. Peer-reviewed original research articles in English reporting maternal alcohol use and diagnosed atopic dermatitis in offspring will be included. Data extraction will comprise study characteristics, exposure timing and measurement, outcome diagnostic criteria and age of assessment, key findings, and reported biological mechanisms. The preliminary findings will be validated through consultation with clinical stakeholders, including experts in allergy medicine, paediatricians, dermatologists, psychiatrists and obstetricians, to maximise the review’s relevance and to identify practical implications for antenatal care and paediatric dermatology. Results will be presented through narrative synthesis, following PRISMA-ScR guidelines, to identify evidence gaps and inform future research and policy.

Alterations in sensory and motor nerve conduction associated with age and osteoarthritis in cats are correlated with functional impairment and somatosensory sensitization

Abstract Feline somatosensory impairments associated with aging and osteoarthritis (OA) can be quantified through quantitative sensory testing and nerve conduction (NC). This prospective, randomized and blinded study aimed to compare NC in young healthy (CTRL, n  = 6) and older OA (OLD, n  = 12) cats. Under temperature-controlled general anesthesia, amplitude and conduction velocity (CV) of mixed tibial/sciatic and ulnar nerves were measured. Structural changes (radiographic score), functional alterations [MI-CAT(V)], neuro-sensitization [paw withdrawal threshold (PWT); and response to mechanical temporal summation (RMTS)] were assessed. Data distribution determined tests for inter-group comparison, and outcome correlations (α = 5%). OLD cats presented higher radiographic and MI-CAT(V) scores, but lower PWT, RMTS, motor CV (–23%), motor (–35%) and sensory (–45%) amplitudes compared to CTRL. Functional alterations correlated strongly with structural changes ( r  = 0.74, p  < 0.001) and age ( r  = 0.90, p  < 0.001), and moderately with neuro-sensitization ( p  < 0.016). Radiographic and MI-CAT(V) scores correlated negatively with (distal) motor CVs ( p  < 0.044), and with some motor and sensory amplitudes ( p  < 0.028). The PWTs correlated positively to motor CVs ( p  < 0.045). Older OA cats exhibited NC alterations correlated with neuro-sensitization and higher than expected with age alone.

Caputo fractional-order SVIR model for rotavirus: Numerical solutions using Laplace-Adomian decomposition method

Rotavirus is a leading cause of severe gastroenteritis and diarrheal mortality in children under five years of age, especially in developing countries. Mathematical modeling plays a crucial role in understanding the transmission dynamics of rotavirus and in evaluating the impact of vaccination strategies. In this study, a Caputo fractional-order susceptible–vaccinated–infected–recovered (SVIR) epidemic model is proposed to explore the transmission dynamics of rotavirus while capturing memory and hereditary effects associated with disease progression and immune response. The disease-free and endemic equilibrium points of the model are derived, and the vaccination reproduction number R v is obtained using the next-generation matrix technique. Stability analysis is performed for the disease-free and endemic equilibrium points. In addition, a comparative study for R v < 1 and R v > 1 is presented. The sensitivity of the model parameters is computed, and the results are presented graphically. Also, the positivity and boundedness of the solutions are verified to ensure biological feasibility. The approximate solutions of the Caputo fractional-order SVIR model are obtained using the Laplace Adomian Decomposition Method (LADM). The stability, convergence, and error analysis of this well-established method are also studied. To validate the obtained solutions, the method is compared with other methods in the classical-order case. Additionally, the LADM solutions are presented numerically and graphically for different fractional orders, showing that reducing the fractional-order parameters increases memory effects and significantly changes the epidemic dynamics. The numerical and graphical results confirm that the fractional-order framework captures the dynamics of the proposed model more effectively than the corresponding classical integer-order epidemic model.

Associations of high-carbohydrate and high-fat dietary patterns with obesity in Thai adults: A cross-sectional analysis with gender comparisons

Accuracy of the molecular diagnosis of duchenne and becker muscular dystrophy: A systematic review with meta-analysis

Introduction Recently, Molecular diagnosis of Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) has become increasingly important in the management of these patients, with techniques such as multiplex ligation-dependent amplification (MLPA) and next-generation sequencing (NGS) coming to the fore. Therefore, this study aims to evaluate the diagnostic accuracy of MLPA, NGS, and the algorithm MLPA-NGS for confirmatory diagnosis of DMD/BMD. Methods We systematically searched databases (PubMed, Embase, Scopus, Cochrane and Web of Science) until July 2025 for studies evaluating the diagnostic accuracy of MLPA and/or NGS testing in patients with clinical suspicion of DMD, considering multiplex PCR or biopsy as the reference test. A meta-analysis was performed using a random-effects model to estimate the sensitivity, specificity, and detection rate of each test. The QUADAS-2 tool was used to assess the risk of bias and the GRADE criteria were used to identify the certainty of evidence. Results We included 10 studies (3786 patients) evaluating the use of MLPA and 14 studies (4333 patients) evaluating the use of NGS. For MLPA, the sensitivity was 0.80 (95%CI: 0.76–0.84; I 2 : 86%), the specificity was 0.93 (95%CI: 0.87–0.96; I 2 : 16%), and AUC 0.90 (CI-95%: 0.89–0.92). For NGS, the detection rate was 0.77 (95% CI: 0.61–0.87; I 2 : 94%). Furthermore, the detection rate increased to 0.97 (95% CI: 0.94–0.99; I 2 : 95%) when NGS was performed after MLPA. We observe a low risk of bias but with very low certainty in the estimations. Conclusions In patients with clinical suspicion of DMD, the MLPA test is very good but with very low certainty. However, in these patients with a negative MLPA, adding the NGS test would allow improve the detection rate. Therefore, the sequential use of these tests could be considered in patients who persist in the clinical suspicion.

Safety and efficacy of the combination of hyperbaric oxygen and 177Lu-DOTA-IBA in treating metastatic bone pain due to tumors

Emerging role of human endogenous retroviruses in mothers with history of perinatal depression and risk of neurodevelopmental disorders in offspring: Results from a pilot study

Perinatal depression (PD) actually affects 10−15% of pregnant women and represents one of the most debated topics as potentially implicated in offspring neurodevelopmental disorders etiology, particularly Autism Spectrum Disorder (ASD). Scientific evidence supports the role of Human Endogenous Retroviruses (HERVs) in ASD, as a link among environmental stimuli, epigenetic remodeling and biological processes. The aim of the present study was to characterize the expression profile of different HERVs and selected cytokines in peripheral blood mononuclear cells from women who have experienced PD in comparison to women without history of PD and their respective children stratified according to ASD diagnosis, by RT Real-Time PCR. We showed that ASD children and their PD mothers share abnormal expression of pHERV-W, syncytin-2 and IL-6 likely influenced by the common environment, maternal status, genetic predisposition, or postnatal factors. Of note, mothers with a history of PD were also evaluated at the time of blood sampling using the Hamilton Depression Rating Scale, and a positive correlation with pHERV-W levels was observed. Together with previous results in preclinical models and human studies, our results support the role of HERVs in autism as a contributing factor in creating an adverse environment for normal neurodevelopment, strengthening the view of a mother-child association in the context of autism. PD being associated with the altered activity of HERVs could be considered to be an additional risk factor in the pathogenesis of autism.

A unified framework for net effects in signed social and ecological networks

Abstract With improvements in data resolution and quality, researchers can now represent complex systems as signed, weighted, and directed networks. In this article, we introduce a framework for measuring net and indirect effects without simplifying these information-rich networks. It captures both direct and indirect interactions, the effect of the whole network on a node, and conversely, the effect of a node on the entire network, while accommodating the complexity of signed, weighted, and directed links. Our taxonomy unifies and extends existing approaches and measures from network science, computational social science, and ecological networks. We demonstrate its value in ecological systems, where net and indirect effects are critical yet difficult to quantify. Using generalized Lotka–Volterra dynamics, we find a strong correlation between negative net effects and species extinction. We further apply the framework to a real-world social network, where it identifies informative rankings that illuminate influence propagation and power dynamics.

Associations between self-reported symptoms and circulating protein biomarkers: A scoping review protocol

Background Studies linking self-reported symptoms to circulating protein biomarkers are increasing, partly driven by the rising number of protein biomarkers being identified. Despite research advances, current reviews that synthesise these studies are typically disease-specific. A broader, diagnosis-agnostic and multidisciplinary scoping review can uncover shared biological patterns associated with symptoms across different conditions and can generate insights that advance precision health and symptom science. This scoping review protocol builds on this need for a broad approach as it aims to consolidate current knowledge on self-reported symptom and circulating protein biomarker associations, identify potential patterns, and provide relevant insights for clinical practice and future research. Methods The protocol is aligned with the PRISMA and JBI guidelines for scoping reviews. The search strategy includes original peer-reviewed journal research articles examining associations between self-reported symptoms and protein biomarkers in blood plasma or serum. Searches will be conducted from PubMed, CINAHL, Embase, and Web of Science databases. A preliminary search retrieved more than 30,000 articles, prompting a pilot test of the Artificial Intelligence (AI)-assisted review screening tool ASReview. The pilot demonstrated time savings, refined methodological decisions, and confirmed the feasibility of proceeding with the review. Therefore, screening will be conducted using ASReview, with a total of five reviewers involved in the process. Data extraction will focus on single self-reported symptoms and circulating protein biomarker pairs that have a reported association. Analysis will involve counting and mapping these associations to identify potential patterns. The protocol was registered with the Open Science Framework (OSF) https://osf.io/bku3f . Discussion This protocol provides a structured and transparent approach for conducting a large-scale scoping review. By adhering to established guidelines, the protocol provides a more comprehensive, standardised, exact, and reproducible accumulation of knowledge, while acknowledging potential limitations. The expected results can contribute to summarise the current understanding of associations between self-reported symptoms and circulating protein biomarkers. This fosters the integration of symptom science and the omics field, specifically proteomics, to advance precision health.