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An improved A* algorithm for generating four-track trajectory planning to adapt to longitudinal rugged terrain

Evaluation of psychiatric conditions in asymptomatic outpatient clinic patients

Introduction A significant part of the internal medicine outpatient clinic burden consists of patients who are asymptomatic and intend to have routine check-up tests. In this study, we aimed to investigate the relationship between visit frequency within a year and the undiagnosed anxiety, depressive mood or obsessive-compulsive disorder. Methods We included in our study 129 participants who applied for routine check-up tests to our hospital’s internal medicine outpatient clinic, without any complaint and known diseases. Individuals were divided into two groups: Group 1 comprised individuals who applied once a year, whereas Group 2 included those who applied more than once a year. Participants underwent routine blood testing, and their mental health was assessed with the Beck`s Depression Inventory (BDI), Beck`s Anxiety Inventory (BAI), and Vancouver Obsessinal Compulsive Inventory (VOCI). Results 66% of the 129 participants included in the study were female (n = 85/44, p < 0.001). When laboratory parameters were examined, no significant difference was found except serum vitamin D levels (14.5/19.8 µg/L, p = 0.024, respectively). BDI and BAI scores were statistically significantly higher in Group 2 (10/14, p = 0.032, 11/13.5, p = 0.027, respectively). There was no difference between the two groups in terms of VOCI scores. Conclusion Asymptomatic patients who are visiting clinics for routine checkups constitute a significant part of the outpatient clinic workload. Assessing the mental health of patients who are attending frequently might be helpful in reducing this burden as well as in diagnosing and initiating treatment of undiagnosed underlying mental disorders. To ensure timely referrals of these patients to psychiatry, an adequate referral system and awareness of early signs of anxiety and depression among healthcare professionals are needed.

The role of RNA structural motifs in RNA-lipid raft interaction

Effects of pressure on the survival and viability of cancer cells in vitro: An analytical study

Intense cancer research is underway to discover possible therapies but no major breakthrough appears to be in sight in terms of its cure when diagnosed late. The cytostatic and growth inhibitory effect of high pressure on cells is well documented. In the present study, two cancer cell lines viz. MDA-MB-231 (breast carcinoma) and A549 (lung carcinoma) and one normal cell line (Vero) were subjected to increased pressure of 18 psi in a specially constructed pressure chamber. It was found that a pressure of 18 psi induced a significant change in the growth parameters of both cancer cell lines versus normal cells. Exposure to increased pressure greatly increased the proportion of MDA-MB-231 cells in the S phase while concurrently reducing the number of cells in the G0/G1 phase as compared to their untreated counterparts. SEM and AFM analysis revealed presence of characteristic ‘pores’ and ‘pits’ on the cell surface of pressure-treated versus untreated cancer cells. TEM analysis also revealed significant intracellular differences between pressure-treated and untreated cancer cells. Hyperbaric nitrogen therapy is proposed as a novel cancer-treatment modality involving administration of N2 at the tumor site in murine models of breast and lung cancer. This would eventually pave the way for development of a device effective treatment strategy for human tumors in future.

Mechanism of calcitonin gene related peptide against acute pancreatitis in rats by modulating amino acid metabolism based on metabonomics

Astragalus polyphenols attenuates doxorubicin-induced cardiotoxicity by activating the PI3K/AKT/NRF2 pathway

Background Doxorubicin (DOX) is a powerful chemotherapeutic agent commonly employed in cancer treatment. However, its clinical utility is constrained by dose-dependent cardiotoxicity, which can result in heart failure and sudden cardiac death. The molecular mechanisms of DOX-induced cardiotoxicity (DIC) include oxidative stress, mitochondrial dysfunction, and the activation of cell death pathways, including ferroptosis. There is an urgent need for effective therapeutic strategies to mitigate DIC. Methods This study investigates the cardioprotective effects of Astragalus Polyphenols (ASP), a bioactive compound extracted from Astragalus membranaceus. In the context of DIC, we utilized AC16 and H9C2 cardiomyocytes to establish a DIC model and assessed the effects of ASP on cell viability, oxidative stress, mitochondrial function, and the PI3K/AKT/NRF2 signaling pathway. The expression of atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP), markers of cardiac injury, was also evaluated. Results ASP treatment significantly reversed DOX-induced reductions in cell viability and mitochondrial membrane potential (MMP) while also decreasing the levels of reactive oxygen species (ROS). Additionally, ASP also downregulated the expression of ANP and BNP, indicating a protective effect on cardiomyocytes. Furthermore, ASP activated the PI3K/AKT/NRF2 pathway, which was suppressed by DOX. Inhibition of this pathway using LY294002 and ML385 abolishes the protective effects of ASP, suggesting that ASP mediates its effects through the PI3K/AKT/NRF2 signaling axis. Conclusion ASP exhibits a protective effect against DOX-induced cardiotoxicity by regulating the PI3K/AKT/NRF2 pathway to reduce oxidative stress and preserve mitochondrial function. These findings suggest that ASP may serve as a potential therapeutic agent to alleviate DIC. Our results provide a novel strategy to protect the heart in patients undergoing DOX chemotherapy.

Multi-material 3D printed composites inspired by nacre: a hard/soft mechanical interplay

Abstract Structural materials are used extensively in nature where mechanical function is required. These structures are composites consisting of soft and, in some cases, hard phases precisely distributed over different length scales. Bio-inspiration aims at producing materials with structure, design and/or mechanical properties adopted from biological tissues. To reproduce complex structures found in nature, additive manufacturing (AM) using three-dimensional printing (3DP) is an attractive method to assemble complex topologies with resolutions approaching the micro and nano-composition. Specifically, high-resolution MultiJetPrinting (MJP) 3D printing allows the simultaneous deposition of soft and hard photo curable plastic resins. Nacre is a prevalent example of a complex biological composite material organization that can test the ability of MJP to manufacture a bio-inspired engineering structure, where the organization of materials in nacre is optimized to avoid catastrophic failure. The ability to generate complex 3D organizations required to mimic the structure of nacre by controlled organization of soft and hard materials is achieved here using a generative design approach. Such a generative design is further enhanced by incorporating two differing MJP directions that provide relatively strong and weak interfaces between the soft and hard material phases. Consideration of classical stress transfer theory between at a hard material reinforcement interface was shown to correlate with experimental observations of mechanical performance and failure in 3D printed nacre inspired composites. Thus, the ability to distribute materials with a range of mechanical properties and incorporate further interfacial design is demonstrated. The approach presented is flexible and allows complex bio-inspired composites to be 3D printed that incorporate different interfacial quality through changing printing direction.

Influence of new qualitative productivity forces on quality-effective change in China’s Yangtze river economic belt sports industry: The mediating effect of industry–University–Research Cooperation

Due to the lack of empirical research on the influence of new qualitative productivity forces on quality-effective change in the sports industry, entropy-weighted threshold-based estimation (TOPSIS) is used based on panel data for 11 provinces and cities in China’s Yangtze River Economic Belt from 2016–2022. The results are used to measure the levels of new qualitative productivity forces and quality-effective change in the sports industry and to analyze the relationships among these factors and industry–university–research cooperation through a bidirectional fixed effects model and a mediating effects model. The study reveals that new qualitative productivity forces have a significant positive effect on quality-effective change in the sports industry that is heterogeneous by region. Industry–university–research cooperation plays a partially intermediary role in promoting quality-effective change in the sports industry through new qualitative productivity forces. In this context, we propose the following measures: focus on cultivating new-quality industries and strengthening their application in the sports industry, emphasize the intermediary effect of industry–university–research cooperation to promote quality-effective change in the sports industry, formulate strategies according to local conditions, and focus on the development of new qualitative productivity forces in sports.

Light-induced negative differential resistance and neural oscillations in neuromorphic photonic semiconductor micropillar sensory neurons

Consumption of protect and risk food groups for non-communicable diseases among women of reproductive age in rural areas of Morogoro, Tanzania

Malnutrition has been persistently high in Tanzania, especially in the rural areas. Although some interventions have been implemented to reduce the rate of undernutrition, improvement is much slower than expected. Moreover, the prevalence of overweight and obesity among women of reproductive age has been on the increase. Changes in lifestyles specifically in eating habits may contribute to the observed increase trend in the prevalence of overweight and obesity. However, there are limited studies that have assessed diet quality for women. Hence, this study aimed to assess the consumption of protective and risk food groups for non-communicable diseases (NCDs) in rural areas of the Morogoro region, Tanzania. The cross-sectional study involved 512 randomly selected women of reproductive age in Mvomero district. All mothers or caretakers with children of age 6–23 months who resided in the area for over three months were eligible to participate. A structured questionnaire was used to collect demographic data and the Global Diet Quality Questionnaire was used to collect dietary intake data for women. A multivariate regression model was used to identify factors associated with consumption of diversified diets, NCD-protect, and NCD-risk food group scores. The results show that about 42% of the women had no formal education and about one in three women own a mobile phone. About 70% consumed vegetables while 33% consumed deep fried foods. Only 34% of the women met the minimum diet diversity (MDD-W) of five or more food groups. The mean NCD-protect score was 2.8 ± 1.4 and the NCD-risk score was 0.77 ± 0.97. Household income was positively associated with an increase in both protect scores and NCD-risk. Mobile phone ownership was positively associated with NCD-risk. Other factors such as age and self-employment in agriculture were positively associated NCD-protect while the number of children was negatively associated with NCD-protect score. Rural communities should be educated on the importance of food diversification starting from production to consumption and the need for multiple sources of income to increase purchasing power of the household while considering proper food choices to avoid the risk of NCDs. The Ministry of Agriculture and other stakeholders should support and promote production of bio-fortified crops and keeping small animals. The Ministry of Education should ensure that school children are aware of the NCD-risk foods and make available healthier food choices around the school environment.

Multilayer analysis of ethnically diverse blood and urine biomarkers for breast cancer risk and prognosis

RETRACTED: Enhancing the decision optimization of interaction design in sustainable healthcare with improved artificial bee colony algorithm and generative artificial intelligence

With the development of digital health, enhancing decision-making effectiveness has become a critical task. This study proposes an improved Artificial Bee Colony (ABC) algorithm aimed at optimizing decision-making models in the field of digital health. The algorithm draws inspiration from the dual-layer evolutionary space of cultural algorithms, combining normative knowledge from the credibility space to dynamically adjust the search range, thereby improving both convergence speed and exploration capabilities. Additionally, a population dispersion strategy is introduced to maintain diversity, effectively balancing global exploration with local exploitation. Experimental results show that the improved ABC algorithm exhibits a 96% convergence probability when approaching the global optimal solution, significantly enhancing the efficiency and accuracy of medical resource optimization, particularly in complex decision-making environments. Integrating this algorithm with the Chat Generative Pre-trained Transformer (ChatGPT) decision system can intelligently generate personalized decision recommendations and leverage natural language processing technologies to better understand and respond to user needs. This study provides an effective tool for scientific decision-making in digital healthcare and offers critical technical support for processing and analyzing large-scale medical data.

Change trends in serum phosphate levels predict in-hospital mortality in critically ill septic patients

Machine learning for predicting antimicrobial resistance in critical and high-priority pathogens: A systematic review considering antimicrobial susceptibility tests in real-world healthcare settings

Background Antimicrobial resistance (AMR) poses a worldwide health threat; quick and accurate identification of AMR enhances patient outcomes and reduces inappropriate antibiotic usage. The objective of this systematic review is to evaluate the efficacy of machine learning (ML) approaches in predicting AMR in critical and high-priority pathogens (CHPP), considering antimicrobial susceptibility tests in real-world healthcare settings. Methods The search methodology encompassed the examination of several databases, such as PubMed/MEDLINE, EMBASE, Web of Science, SCOPUS, and SCIELO. An extensive electronic database search was conducted from the inception of these databases until November 2024. Results After completing the final step of the eligibility assessment, the systematic review ultimately included 21 papers. All included studies were cohort observational studies assessing 688,107 patients and 1,710,867 antimicrobial susceptibility tests. GBDT, Random Forest, and XGBoost were the top-performing ML models for predicting antibiotic resistance in CHPP infections. GBDT exhibited the highest AuROC values compared to Logistic Regression (LR), with a mean value of 0.80 (range 0.77–0.90) and 0.68 (range 0.50–0.83), respectively. Similarly, Random Forest generally showed better AuROC values compared to LR (mean value 0.75, range 0.58–0.98 versus mean value 0.71, range 0.61–0.83). However, some predictors selected by these algorithms align with those suggested by LR. Conclusions ML displays potential as a technology for predicting AMR, incorporating antimicrobial susceptibility tests in CHPP in real-world healthcare settings. However, limitations such as retrospective methodology for model development, nonstandard data processing, and lack of validation in randomized controlled trials must be considered before applying these models in clinical practice.

A black-winged kite optimization algorithm enhanced by osprey optimization and vertical and horizontal crossover improvement

Evaluating refrigeration and antibiotic treatment for maintaining urine electrophysiology

Background Electrophysiological analysis of urine has shown utility in differentiating between healthy and bladder cancer specimens, offering a rapid, label-free alternative to molecular methods. However, transporting and preserving urine samples from collection to the laboratory poses logistical challenges that could impact the reliability of electrophysiological measurements. Objective This study investigates the effects of prolonged refrigeration on the dielectric properties and ζ-potential of urine specimens and evaluate whether antibiotic treatment can enhance sample preservation without altering electrophysiological properties. A new methodology to evaluate urine specimen quality and determine bacterial contamination, using electrophysiological modalities, is presented. Methods Mid-stream urine samples from healthy participants (n =  4) were collected and divided into untreated and 1% penicillin/streptomycin-treated groups. Samples were analysed at baseline prior to storage at 4°C, with further analysis every 24 hours for 96 hours. Changes in dielectrophoresis (DEP) response and ζ-potential were measured using a 3DEP cytometer (Deparator, UK) and Malvern Panalytical Zetasizer Nano ZS90 (Malvern, UK), respectively. Chemical analyses, including pH and nitrite levels, and microscopic examinations were also conducted. Results & Limitations Significant electrophysiological changes were observed in both untreated and antibiotic-treated urine samples over time. Both groups showed a linear increase of change in DEP response and ζ-potential values, from baseline over time. Untreated samples exhibited significant deviations in DEP and ζ-potential from baseline after 48 hours, with significance at 72 hours (P < 0.05). Treated samples only showed significant changes in ζ-potential at 96 hours (P < 0.05). Chemical analysis indicated increased pH and nitrite presence in untreated samples at 48 hours, indicating bacterial growth. Treated samples took more than 48 hours to show changes in both chemical parameters. Limitations include the relatively small study sample size, not evaluating the preservatory effects of UTI-specific antibiotics, such as nitrofurantoin and trimethoprim, and exploring different drug concentrations. Conclusion Prolonged refrigeration can maintain the quality of urine samples for up to 48 hours with antibiotic treatment. Current UK and European guidelines recommend urinalysis within 24 hours of specimen collection; the findings of this study support the use of DEP and ζ-potential analysis as practical clinical tests in a mail-in screening setting, provided appropriate sample preservation measures are taken.

Assessing the effectiveness of long short-term memory and artificial neural network in predicting daily ozone concentrations in Liaocheng City

Soluble RAGE enhances muscle regeneration after cryoinjury in aged and diseased mice

The Receptor for Advanced Glycation End Products (RAGE), classically considered a mediator of acute and chronic inflammatory responses, has recently been implicated by genetic knockout studies as a regulator of skeletal muscle physiology during development and following acute injury. Yet, the role of its soluble isoform, soluble RAGE (sRAGE), in muscle regeneration remains relatively unexplored. To address this knowledge gap, Adeno-Associated Virus (AAV) mediated and genetic knockin supplementation strategies were developed to specifically assess the effects of changing levels of sRAGE on muscle regeneration. We evaluated general muscle physiology and histology, including central nucleation, and myofiber size. We found that acute induction of sRAGE in aged and atherosclerotic animals accelerates muscle repair after cryoinjury. Similarly, genetic modification of the endogenous Ager gene locus to favor production of sRAGE over transmembrane RAGE accelerates repair of cryo-damaged skeletal muscle. However, increasing sRAGE via AAV delivery or using our transgenic mouse lines had no impact on muscle repair in aged or diseased mice after barium chloride (BaCl2) injury. Together, these studies identify a unique muscle regulatory activity of sRAGE that is variable across injury models and may be targeted in a context-specific manner to alter the skeletal muscle microenvironment and boost muscle regenerative output.

Phytochemical analysis of Asclepias syriaca L. leaf extract and its potential phytotoxic effect on some invasive weeds

The 24-hour movement behaviour compositions of children with and without impaired motor coordination: The Moves-UP project

The 24-hour movement behaviours, including sleep, sedentary behaviour (SB), and moderate-to-vigorous physical activity (MVPA) are crucial for a child’s healthy growth and development. Yet, the full 24-hour movement behaviour composition has not been thoroughly explored in children with suspected Developmental Coordination Disorder (sDCD). The aim of this study was to compare the 24-hour movement behaviour compositions of children with sDCD to their typically developing (TD) peers and to assess the associations between movement behaviours and motor competence. Sixty-nine children (mean age 8.6 ±  1.6 years, 55% boys) wore a wrist-mounted accelerometers for seven consecutive days, completed a dynamic motor competence assessment and were screened for sDCD using the Developmental Coordination Disorder Questionnaire. Results of the compositional Isotemporal-substitution analysis indicated that children with sDCD spent less time in light physical activity (LPA) and MVPA and more time in SB compared to the TD group. No significant differences were observed during school or weekend periods. However, increasing MVPA in place of lower-intensity activities was associated with theoretical improvements in motor competence. The 24-hour movement behaviour profiles of children with sDCD identified in this study may have adverse implications for their future health and wellbeing, emphasising the need for targeted interventions, particularly during out-of-school hours.