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ADIBAS-Volterra aircraft trajectory prediction model based on improved dynamic integration of beetle tentacle searching
The prediction of aircraft manoeuvre trajectories is an important prerequisite for decision making. However, how to achieve real-time and scientific aircraft manoeuvre trajectory prediction using trajectory data needs to be addressed urgently. To solve this problem, we propose a hybrid algorithm based on Improved Beetle Antennae Search (BAS), Aircraft Manoeuvre Boundary Point Identification algorithm, Adaptive Dynamic Integration (ADI) and Volterra series, called ADIBAS-Volterra. Firstly, a large amount of trajectory sample data is trained to construct the BAS-Volterra algorithm suitable for predicting aircraft manoeuvre trajectories, which achieves a balance between global and local solutions. Secondly, in order to improve the accuracy of the online manoeuvre trajectory prediction of our proposed model in complex environments, the parameters of the whole prediction model based on the BAS-Volterra algorithm are adaptively updated according to the identification results of the aircraft manoeuvre boundary points, including the optimisation of the algorithmic weights and the optimisation of the parameters. Compared with the existing state-of-the-art methods, the newly proposed aircraft manoeuvre trajectory prediction algorithm adopts K-means clustering to initialise the tentacle position, which can flexibly adjust the search strategy at different stages and make the algorithm more reasonable. Four measures, Relative Root Mean Square Error (RRMSE), Mean Absolute Deviation (MAD), Mean Absolute Percentage Error (MAPE) and Normalised Mean Square Error (NMSE) were used to assess prediction accuracy. Finally, the scientific validity of the proposed algorithm is verified using Mackey Glass and Rossler datasets.
Implications of Yedoma bank outcrop on the Arctic river sediment transport
Utility of artificial intelligence-based conversation voice analysis for detecting cognitive decline
Recent developments in artificial intelligence (AI) have introduced new technologies that can aid in detecting cognitive decline. This study developed a voice-based AI model that screens for cognitive decline using only a short conversational voice sample. The process involved collecting voice samples, applying machine learning (ML), and confirming accuracy through test data. The AI model extracts multiple voice features from the collected voice data to detect potential signs of cognitive impairment. Data labeling for ML was based on Mini-Mental State Examination scores: scores of 23 or lower were labeled as “cognitively declined (CD),” while scores above 24 were labeled as “cognitively normal (CN).” A fully coupled neural network architecture was employed for deep learning, using voice samples from 263 patients. Twenty voice samples, each comprising a one-minute conversation, were used for accuracy evaluation. The developed AI model achieved an accuracy of 0.950 in discriminating between CD and CN individuals, with a sensitivity of 0.875, specificity of 1.000, and an average area under the curve of 0.990. This voice AI model shows promise as a cognitive screening tool accessible via mobile devices, requiring no specialized environments or equipment, and can help detect CD, offering individuals the opportunity to seek medical attention.
The dual effects of iron deficiency on intervertebral disc development and on acute injury-induced disc degeneration
Accuracy of refractive error measurements in children with strabismus comparing cycloplegic autorefractometry to dry monocular Mohindra retinoscopy
Objective Uncorrected or undercorrected refractive errors affect 153 million individuals globally, leading to vision impairment and associated quality of life issues. Accurate measurement of refractive errors in children especially with strabismus is critical for effective management. This study evaluates the agreement between near retinoscopy (Mohindra retinoscopy) and cycloplegic autorefractometry in measuring refractive errors among children diagnosed with strabismus. Methods Forty-three strabismic children (18 males, 25 females; ages 3–10 years; mean age 5.5 yo) underwent refractive error evaluations using both methods: Mohindra retinoscopy and cycloplegic autorefractometry. The study assessed spherical component, spherical equivalent, cylinder power, and cylinder vectors J0 and J45. Statistical analyses, including Wilcoxon test Student’s t-test, Bland-Altman analysis, Intraclass Correlation Coefficient (ICC) analysis and correlations (supplementary analysis) evaluated differences, correlations and agreement between the two methods. Results The median spherical component of refractive error was almost equal for both methods used (+4.38 D vs. + 4.50, for Mohindra retinoscopy and cycloplegic autorefractometry, respectively; P = .54), as well as median spherical refractive equivalent (+4.25 for both methods; P = .29). Mean spherical components of refractive errors were nearly identical across both methods, showing Mohindra retinoscopy provided slightly higher hyperopic measurements (0.03 D more positive), whereas spherical equivalent of refractive error showed 0.07 D more positive results for Mohindra retinoscopy than cycloplegic autorefractometry. Median cylinder powers were the same for both methods (-0.50 D; P = .25). No differences were also found for J0 (P = .91) and J45 vectors (P = .88) between Mohindra retinoscopy and cycloplegic autorefractometry. Conclusions Near retinoscopy demonstrates comparable accuracy to cycloplegic autorefractometry in children with strabismus. These findings suggest that Mohindra retinoscopy may be used effectively without the need for cycloplegic intervention during follow-up visits, though further research is warranted to confirm its applicability.
Modified starch as a new co-excipient in hydrophilic gels for prolonged drug delivery
Readiness to the privatization of the health system in Saudi Arabia: Translation and factor analysis of Readiness to Organizational change (ROC) scale
Background The Kingdom of Saudi Arabia (KSA) began a major transformation as a part of version 2030 for its health system. These reform initiatives aim to privatize health services and improve efficiency. Despite this meaningful change, there is a knowledge gap in how healthcare providers prepare for or perceive this shift. Specifically, there has been a lack of validation of Arabic instruments that gauge the individual readiness to this change. This study bridges the gap by localizing and validating the Readiness to Organizational Change scale (ROC) to provide empirical evidence and to understand adaptability for the KSA context. Method The study aimed to test and validate a tool that can be used to assess the ability of individuals to embrace the change initiatives among healthcare providers. A cross-sectional study was conducted in a public healthcare setting that included allied healthcare providers and physicians and excluded the administration staff. Ethical approval was obtained, and the questionnaire was distributed among participants electronically. Result There were 296 participants who completed the survey, with (78.0%) being male and they were between 25–35 years old, while the females represented (22%). The majority had less than 10 years’ experience and were married (88.2%). The face and content validity showed an excellent result for Arabic context S-CVI/AVE = 0.97. The inter-item correlation revealed a significant value (p < 0.001), which confirmed convergent validity, and Factor analysis assessed the adequacy of sampling (KMO = 0.77). The Exploratory Factor Analysis (EFA) extracted seven factors describing 74.6% of the total Variance, with an adequate value of commonalities for most items. Conclusion The Arabic version of ROC is a valid and reliable scale for assessing readiness among healthcare providers in the context of KSA. This translated version can provide insightful information and facilitate the transition of the health system in KSA and achieve the healthcare vision of 2030.
Exploring the heterogeneity in glioblastoma cellular mechanics using in-vitro assays and atomic force microscopy
Study protocol for a randomized controlled trial comparing pulse pressure variation (PPV) and central venous pressure (CVP) guidance for fluid responsiveness assessment in neurosurgical patients undergoing posterior fossa tumor resection in park bench position
Introduction Suboccipital craniotomy in the park bench position is linked to considerable physiological alterations. Effective fluid management in this context is a challenge to anesthesiologists. No published data exist on pulse pressure variation and central venous pressure guidance in patients undergoing tumor resection in the park bench posture. We undertake a study to evaluate the concept that two approaches of goal-directed fluid treatment enhance optimal fluid management and improve hemodynamic stability. We established the fluid management protocol for this process. Methods and analysis This is a prospective randomized double-blinded study of adult patients undergoing suboccipital craniotomy to remove tumors in the park bench position. The comparison of pulse pressure variation and central venous pressure for fluid management regarding mean intraoperative fluid administration as the primary outcome. A sample size of 54 will yield over 80% power to identify a mean fluid difference of at least 500 ml between two specified methods. The secondary outcomes are data pertinent to fluid administered during and after surgery, including the lowest systolic blood pressure, serum lactate levels, vasopressor utilization, and duration of ICU stay. The statistical analysis will be validated based on the data distribution and types of data. This is the first study to examine two goal-directed fluid therapies, pulse pressure variation and central venous pressure, in patients with posterior fossa tumors and undergoing surgery in the park bench position. Researchers want to contribute novel information to the domain of fluid optimization in neurosurgery. Trial registration ClinicalTrials.gov NCT06595667.
Artistic anti-counterfeiting with a pH-responsive fluorescent ink using DFT and molecular electrostatic potential mapping insights
Abstract The observed fluorescence behavior of the sulfur, nitrogen-doped carbon dots (S, N-CDs) ink which derived from onion peel wastes (OW) demonstrates its pH-sensitive nature, making it suitable for applications where visual or fluorescent changes upon pH variation are desired. The initial lack of fluorescence under UV light suggests that the S, N-CDs in the ink are in a non-fluorescent state. However, upon treatment with acid, the ink exhibits a faint yellow color under light and fluoresces under UV light. This indicates a shift in the electronic structure of the S, N-CDs, likely due to protonation. The return to non-fluorescence after re-treatment with alkaline solution suggests that the de-protonation process reverses the effect of acid, restoring the S, N-CDs to their original non-fluorescent state. This reversible pH-sensitivity is a valuable asset for various applications. The synthesized S, N-CDs exhibited a reversible change in fluorescence intensity under acidic and alkaline conditions, transitioning from non-fluorescent to fluorescent under acidic conditions and back to non-fluorescent in alkaline media. Density Functional Theory (DFT) calculations revealed that S, N-doping resulted in a narrower energy gap (0.2779 eV compared to 0.3199 eV for N-CDs) and a higher dipole moment (2.640 Debye), enhancing their reactivity towards protons and leading to more pronounced color and fluorescence changes across different pH conditions. The S, N-CDs displayed dual fluorescence emission peaks at 443.00 nm and 502.00 nm upon excitation at 350 nm, and fluorescence contour maps (FCM) confirmed their multicolor emission capabilities. The calculated quantum yield for the S, N-CDs was notably high at 37.76%. Fourier Transform Infrared (FTIR) spectroscopy confirmed the successful incorporation of sulfur (S–H at 2368 cm⁻1, C–S at 750 cm⁻1) and nitrogen (N–H at 3552 cm⁻1, C–N at 989 cm⁻1) functionalities into the carbon dot structure. Furthermore, Molecular Electrostatic Potential (ESPM) mapping indicated regions of high negative potential around S, OH, and C=O groups, particularly pronounced under acidic and basic conditions, supporting the observed pH sensitivity.
Identification of potential biomarkers associated with immune cell infiltration patterns in Kawasaki disease via bioinformatics
Inflammation and immune dysregulation play critical roles in Kawasaki disease (KD) pathogenesis, yet specific biomarkers and immune signatures remain elusive. This study aims to identify key biomarkers and characterize immune cell infiltration scores in KD using bioinformatic approaches. The GSE73461 dataset, downloaded from the Gene Expression Omnibus (GEO) database, includes 78 KD patients and 55 normal controls collected by Imperial College London from 2015 to 2023, and was analyzed to identify differentially expressed genes (DEGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed significant involvement of these DEGs in acute inflammatory responses, plasma membrane components, PI3K-Akt signaling, and cytokine interactions. Protein-protein interaction (PPI) network was constructed, and five candidate hub genes (AURKB, BUB1, CCL2, IL-4, and TOP2A) were identified. Immune cell infiltration analysis gusing the XCell algorithm showed increased levels of Monocytes, neutrophils, and other immune cells in KD, while B cells and T cells were decreased. Correlation analysis indicated that these candidate hub genes are associated with immune dysregulation and inflammation in KD. These findings provide potential diagnostic biomarkers and therapeutic targets for KD, warranting further validation in larger studies.
Isolation and characterization of Chitosan from shrimp shell waste and the sustainable preparation of salicylic acid-loaded Chitosan nanoparticles for antibiofilm applications
Abstract Microbial biofilms present a significant global health challenge, as they are associated with severe chronic infections and the emergence of antibiotic resistance. Currently, only a limited number of clinically available drugs effectively target microbial biofilms. This underscores the urgent need for the development of new sustainable therapeutic strategies to address biofilm-associated infections. Developing a sustainable and biodegradable preparation for eradicating microbial biofilms is critically important. In this study, chitosan was extracted from shrimp shell waste and utilized to prepare salicylic acid-loaded chitosan nanoparticles (NPs) using various synthesis methods. The particle size of the prepared nanoparticles ranged from 287.4 to 226.3 nm, with zeta potential values between + 36.6 and + 41.3 mV, indicating good stability. The nanoparticles demonstrated safety, with half maximal inhibitory concentration (IC50) values ranging from 1009 to 1346 µg/mL. The combination of chitosan and salicylic acid exhibited significant antibiofilm activity against Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, and Candida albicans, with particularly high efficacy against Candida albicans, achieving up to 85% biofilm inhibition. While the particle size and antibiofilm activity of the nanoforms showed minimal differences, formulation M4, using sodium alginate, stands out as the most eco-friendly option. This study highlights the potential of bio-sustainable chitosan-based formulations for combating biofilm formation and addressing antimicrobial resistance.
A novel approach for measuring allostatic load highlights differences in stress burdens due to race, sex and smoking status
The psychosocial and environmental stressors resulting from adverse social determinants of health (SDOH) can result in allostatic load, or ‘wear and tear’ on the body due to prolonged stress. Allostatic load serves as a useful tool to measure stress- related biological responses that can be integrated into risk assessments. In this study a novel allostatic load measure was used to investigate the relationship between acute stress, stress-related physiological dysregulation and allostatic load (AL) and various demographic variables. Using a small volume of serum collected from 63 participants, we assessed stress biomarkers through ELISA assays and developed a one-sample, semi-automated method for calculating AL scores derived from the Toxicological Prioritization Index (ToxPi) framework. Our analysis employed ordinal regression models to identify the contributions of primary mediators to predicting blood pressure classification, revealing that epinephrine was the most significant predictor of blood pressure, followed by cortisol. Primarily, our results highlight racial disparities in stress loads, in which Black participants had greater secondary mediator scores, and higher AL compared to White participants. Black females and Black non-smokers had higher physiological dysregulation and allostatic load than White participants. Overall, our study presents a novel scoring approach that facilitates the integration of allostatic load measures from a single clinical sample into environmental health research. It also demonstrates the utility of allostatic load in capturing race and sex differences in stress burdens, with important implications for understanding health disparities and improving risk assessments.
Study of temporal behaviour of meteorological drought using innovative polygon trend and scaling hypothesis methods in Kolasib district, Mizoram, India
Abstract Drought, one of the most frequent water-related disasters, puts a great deal of strain on agriculture and associated activities in all types of climates. North-east India (NEI) having residual rainforests is also affected by this slowly unfolding disaster inspite of this region receiving the highest annual global rainfall. The multi-time scale Standardized Precipitation Index (SPI 1-month and 3-month) was used to determine the prevalence of meteorological drought in Kolasib (having humid subtropical climate, Cwa) site from Mizoram, a mountainous state situated in the southern tip of the NEI. To identify the nature of the drought, an innovative polygon trend analysis (IPTA) along with the change point detection (Pettitt and Pruned Exact Linear Time methods) and the long-term persistence (LTP) of meteorological drought under scaling theory was examined. The highest drought severity, drought duration and interval based on the SPI-1 (SPI-3) at Kolasib were observed as -11.4, 7 months from October, 1990 to April, 1991 and 176 months from March, 1996 to October, 2010 (-34.6, 17 months from December 1989 to April 1991 and 222 months from September, 1993 to February, 2012), respectively. Further, the IPTA analysis was carried out on the SPI-1 (SPI-3) month time series, and the monthly standard deviation obtained indicate that the highest decreasing trend transition occurred from May to June (July to August), i.e., trend slope of -9.45 (slope of -9.6) points of more and stronger drought event’s occurrence in crucial months of monsoon season. The PELT method observed the most drought conditions from June to August and November to January, which were almost similar to the results obtained through the IPTA. Trend analysis of drought events of both SPI-1 and SPI-3 through the LTP revealed that all twelve months observed long–term drought effect in Kolasib. The strongest LTP (Hurst estimate more than 0.90) for the SPI-3 were observed in June to September and November to January, respectively. However, no significant trends exist in the LTP, which indicated a longer drought cyclic pattern in Kolasib. It is evident from these findings that droughts in Kolasib are not only intensifying but also becoming more prolonged, necessitating proactive and science-based policy measures for drought mitigation in the region.
Individual differences in executive functions and theory of mind mediate the relation between academic skills from kindergarten to 5th grade
Individual differences in early academic skills at school entry are known to predict later academic outcomes, as demonstrated primarily by studies conducted in the United States (US). However, the mechanisms underlying this association remain unclear. In a country where early childhood education is more homogeneous than in the US (i.e., France), this study examined the strength of that predictive relationship and explored whether it could be partly explained by two domain-general mechanisms that are fundamental to effective learning in a school context: executive functions and children’s ability to navigate social relationships. We measured math and reading skills in a cohort of 95 French children in both kindergarten and 5th grade, while also assessing their self-regulation, working memory, planning, theory of mind, and social behaviors at one or both time points. Results confirmed within- and cross-domain associations between early and later academic skills that were comparable to those found in previous studies. Self-regulation, working memory, and theory of mind all mediated both within- and cross-domain relationships. However, these mediations were systematically partial, meaning that early measures of academic achievement remained particularly strong predictors of later academic success. These findings suggest that domain-general cognitive processes, such as executive functions and social cognition, may play a role in explaining the relation between early and later academic achievement. However, a significant part of that relation may still be explained by domain-specific skill-building mechanisms.
A logistic regression model to predict the next rabies virus host-shift event
Abstract Rabies virus (RABV) host-shift events (HSEs) are thought to be promoted by viral genomic and ecological factors, but the relative balance of the two is unclear. Using a dataset of 19,170 species pairs that were known or not known to be linked by an HSE, we developed a logistic regression model to explore how biological and ecological characteristics of cross-species infections and their associated RABV variant (RVV) influence HSE risk. The model incorporates relatedness, body temperature, litter size, adult weight, and the broad lineage (bat or canine) of the RABV variant maintained by the reservoir species. Assessed with leave-one-out cross validation, the model identifies known HSEs with 90% accuracy (sensitivity 90%, specificity 82%). The susceptible-reservoir infection on each continent with the highest risk of HSE are coyotes with Canine-associated RVVs (North/Central America, RR = 187.0), culpeos with Canine-associated RVVs (South America, 100.9), dholes with Canine-associated RVVs (Asia, 159.8), arctic foxes with Raccoon Dog RVV (Europe, 115.8), and African wild dogs with Canine-associated RVVs (Africa, 134.8). The results of this model can be used to help predict the next HSE, identify potential cryptic RABV reservoirs, inform contingency actions when a high-risk event is identified, and prepare for importation or incursion events.
Association between arsenic exposure and intrauterine growth restriction: A systematic review and meta-analysis
Several observational studies have explored the link between arsenic (As) exposure and intrauterine growth restriction (IUGR). However, epidemiological findings have been inconsistent, with a wide range of reported heterogeneity. This study aims to systematically evaluate the association between As exposure and IUGR (SGA(Small for gestational age), PTB(Preterm birth), LBW(Preterm birth)) through a meta-analysis. We searched six databases—China National Knowledge Infrastructure, Wan Fang, VIP Database, PubMed, Web of Science, and Science Direct—for studies on As exposure and IUGR up to May 2024. After screening and data extraction, a comprehensive bias risk assessment was conducted using the Newcastle-Ottawa Scale (NOS), AHRQ (the assessment tool of the Agency for Healthcare Research and Quality), and NTP/OHAT (the assessment tool of the National Toxicology Program/Office of Health Assessment and Translation). Meta-analysis was conducted using random-effects models (I2 > 50%) or fixed-effects models (I2 < 50%) to estimate effect sizes. Subgroup analysis and meta-regression analysis were performed to identify the sources of heterogeneity. Publication bias was assessed using the Egger test, Begg test, and funnel plot. Eleven studies, including 2,183,652 participants from the Americas, Europe, Asia, and Africa, were analyzed. Results showed a significant association between As exposure and SGA (OR: 1.06, 95% CI: 1.00, 1.13), particularly in Asia (OR: 1.28, 95% CI: 1.10, 1.49). Maternal exposure to higher As levels (10–100 μg/L) was also significantly associated with SGA (OR: 1.25, 95% CI: 1.04, 1.50). Although PTB (OR: 1.03, 95% CI: 0.99, 1.07) and LBW (OR: 1.03, 95% CI: 0.97, 1.09) did not show overall significant associations, subgroup analyses revealed increased risks under specific conditions. As exposure at 1–10 μg/L significantly increased PTB risk (OR: 1.13, 95% CI: 1.06, 1.21), while exposure at 0–1 μg/L significantly increased LBW risk (OR: 1.13, 95% CI: 1.06, 1.21). This study supports a link between As exposure and increased IUGR risk, particularly SGA. Stricter public health policies are needed to reduce arsenic exposure during pregnancy. However, due to heterogeneity and potential publication bias, results should be interpreted with caution.
Preventive effect of probiotics on periodontal ligament in a rat model of anorexia nervosa
Abstract The rising prevalence of anorexia nervosa (AN), especially among adolescents, and the limited understanding of its effects on the periodontium often hinder decision making in dentistry and periodontology. As an adjunct to periodontal therapy, probiotic administration has shown promising effects on oral health by decreasing pathogen counts and altering the immune response. This study thus investigates changes in morphology and remodelling of alveolar bone and periodontal ligament (PDL) due to an AN-like condition, along with potential protective effects of probiotics, using a rat model. Three-week-old female Wistar rats were divided into three groups: a control group with ad libitum food and two groups undergoing an activity-based anorexia (ABA) model. One ABA group received oral multi-strain probiotics during starvation. After five weeks, all rats were sacrificed for ex-vivo micro-CT scans of the maxilla and mandible to assess alveolar bone and PDL morphology, as well as histological evaluations for PDL fibre vitality and structural organization. The data were statistically evaluated by one-way ANOVA with Tukey’s post-hoc test or by Kruskal–Wallis with Dunn’s test for parametric or nonparametric data, respectively. The results showed no structural changes in alveolar bone caused by either ABA or probiotic treatment; however, the ABA group exhibited a significant reduction in PDL thickness, which could not be reversed by probiotic treatment. Despite this, histological analysis indicated improved connectivity and density of PDL fibres in the probiotic group compared with the ABA-only group. No differences were found between the mandible and maxilla. In conclusion, while probiotics did not prevent PDL thinning, they enhanced its composition/vitality compared to the ABA condition alone.
Morphological and nutritional responses of sorghum to variable irrigation levels and nitrogen doses
This study aimed to determine the effects of different irrigation levels (50%, 75%, and 100% of ETo values calculated using evaporation from Class-A pan) and nitrogen doses (0, 90, 180, and 270 kg ha ⁻ ¹) on yield, yield components, and the nutritional properties of sorghum grains. According to the research results, increasing irrigation and nitrogen fertilization levels enhanced plant height, thousand-grain weight, grain number per panicle, grain weight per panicle, and grain yield. The highest grain yield (7120 kg ha ⁻ ¹) was obtained with 100% irrigation and 180 kg ha ⁻ ¹ N application. While increasing irrigation levels increased oil content, higher nitrogen doses caused a decrease for it. The highest oil content (6.64%) was recorded with 100% irrigation and 0 kg ha ⁻ ¹ N application. Protein content increased with irrigation and nitrogen applications, reaching the highest level (11.85%) with 100% irrigation and 270 kg ha ⁻ ¹ N application. Higher irrigation levels also increased total starch and phytic acid content. Among nitrogen applications, the dose of 270 kg ha ⁻ ¹ resulted in the maximum total starch (77.29%) and phytic acid content (1.83%). The ratio of resistant starch (RS) was found to be high at 50% irrigation with low nitrogen doses, indicating an inverse relationship with the total starch content. Both irrigation and nitrogen applications significantly affected the ratios of oleic and linoleic acids. Specifically, increased irrigation raised the linoleic acid content, while nitrogen applications enhanced the oleic acid content. Additionally, as irrigation levels increased, the contents of potassium (K), magnesium (Mg), iron (Fe), phosphorus (P), and zinc (Zn) also increased. Conversely, the levels of calcium (Ca) and manganese (Mn) decreased. Generally, higher nitrogen doses resulted in increased mineral content, with the highest levels of magnesium, iron, and zinc observed at nitrogen doses between 180 and 270 kg ha ⁻ ¹. According to the research results, the most suitable irrigation level for optimizing high yield and grain nutritional properties was determined to be 100%, with a nitrogen dose of 180–270 kg ha ⁻ ¹. These findings will contribute to future studies on different sorghum varieties under varying climate and soil conditions.