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Abstract Colorectal cancer (CRC) is a prevalent malignant tumor of the gastrointestinal system, with the third and second highest incidence and mortality rates globally in 2020, respectively. Immunotherapy has developed rapidly in recent years. Natural killer (NK) cells have received increasing attention in the field of tumor immunotherapy due to their recognition and killing tumor cells without the limitations of major histocompatibility complexes. However, constraints within the tumor microenvironment that impede the infiltration and proliferation of NK cells result in poor efficacy of NK cell therapy for solid tumors. Oncolytic viral therapy is an immunogenic treatment with the potential to enhance anti-tumour immune responses and promote immune cell infiltration. In this study, we synergistically combine NK cells with an oncolytic adenovirus carrying Decorin (rAd.DCN) for the treatment of colorectal cancer (CRC) in a xenograft mouse model. By using Flow cytometry, real-time quantitative PCR and Calcein-AM release assay, we found that rAd.DCN could effectively promote proliferation, activation and degranulation of NK cells, up-regulate expression and secretion of NK cell killing activity-related factors, and enhance their killing activity. The efficacy is better than that of the blank control oncolytic virus rAd.Null. Combined treatment significantly inhibited tumor growth, increased the number of NK cells in peripheral blood, promoted the killing function of NK cells, and increased the expression levels of perforin and IFN-γ. At the same time, more NK cells were recruited to infiltrate tumor tissue. Our study established the feasibility of combination NK cells and oncolytic adenovirus application, thus expanding the scope of potentially curative treatments for NK cells in CRC.

Abstract Background Internet gaming disorder (IGD), recognized by the World Health Organization (WHO), significantly impacts adolescent mental and physical health. With a global prevalence of 3.05%, rates are higher in Asia, especially among adolescents and males. The COVID-19 pandemic has exacerbated IGD due to increased gaming time from isolation and anxiety. Vulnerable groups include adolescents with poor academic performance, introverted personalities, and comorbid mental disorders. IGD mechanisms remain unclear, lacking prospective research. Based on Skinner’s reinforcement theory, the purpose of this study is to explore the mechanisms of IGD from individual and environmental perspectives, incorporating age-related changes and game features, and to develop intelligent monitoring models for early intervention in high-risk adolescents. Methods This prospective cohort study will investigate IGD mechanisms in middle and high school students in Shenzhen, China. Data will be collected via online surveys and Python-based web scraping, with a 3-year follow-up and assessments every 6 months. Unstructured data obtained through Python-based web scraping will be structured using natural language processing techniques. Collected data will include personal characteristics, gaming usage, academic experiences, and psycho-behavioral-social factors. Baseline data will train and test predictive models, while follow-up data will validate them. Data preprocessing, normalization, and analysis will be performed. Predictive models, including Cox proportional hazards and Weibull regression, will be evaluated through cross-validation, confusion matrix, receiver operating characteristic (ROC) curve, area under the curve (AUC), and root mean square error (RMSE). Discussion The study aims to understand the interplay between individual and environmental factors in IGD, incorporating age-related changes and game features. Active monitoring and early intervention are critical for preventing IGD. Despite limitations in geographic scope and biological data collection, the study’s innovative design and methodologies offer valuable contributions to public health, promoting effective interventions for high-risk individuals.

Abstract Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial ecosystems, but its global importance remains uncertain. Accurately modeling and predicting CUE on a global scale is challenging due to inconsistencies in measurement techniques and the complex interactions of climatic, edaphic, and biological factors across scales. The link between microbial CUE and soil organic carbon relies on the stabilization of microbial necromass within soil aggregates or its association with minerals, necessitating an integration of microbial and stabilization processes in modeling approaches. In this perspective, we propose a comprehensive framework that integrates diverse data sources, ranging from genomic information to traditional soil carbon assessments, to refine carbon cycle models by incorporating variations in CUE, thereby enhancing our understanding of the microbial contribution to carbon cycling.

Long-term research in grassland biodiversity experiments has provided empirical evidence that ecological and evolutionary processes are intertwined in determining both biodiversity–ecosystem functioning (BEF) and biodiversity–stability relationships. Focusing on plant diversity, we hypothesize that multifunctional stability is highest in high-diversity plant communities and that biodiversity–stability relationships increase over time due to a variety of forms of ecological complementarity including the interaction with other biota above and below ground. We introduce the multiple-mechanisms hypothesis of biodiversity–stability relationships suggesting that it is not an individual mechanism that drives long-term biodiversity effects on ecosystem functioning and stability but that several intertwined processes produce increasingly positive ecosystem effects. The following six mechanisms are important. Low-diversity plant communities accumulate more plant antagonists over time (1), and use resources less efficiently and have more open, leaky nutrient cycles (2). Conversely, high-diversity plant communities support a greater diversity and activity of beneficial interaction partners across trophic levels (3); diversify in their traits over time and space, within and across species, to optimize temporal (intra- and interannual) and spatial complementarity (4), create a more stable microclimate (5), and foster higher top-down control of aboveground and belowground herbivores by predators (6). In line with the observation that different species play unique roles in ecosystems that are dynamic and multifaceted, the particular mechanism contributing most to the higher performance and stability of diverse plant communities might differ across ecosystem functions, years, locations, and environmental change scenarios. This indicates “between-context insurance” or “across-context complementarity” of different mechanisms. We introduce examples of experiments that will be conducted to test our hypotheses and which might inspire additional work.

Genome-scale metabolic models (GEMs) have been widely employed to predict microorganism behaviors. However, GEMs only consider stoichiometric constraints, leading to a linear increase in simulated growth and product yields as substrate uptake rates rise. This divergence from experimental measurements prompted the creation of enzyme-constrained models (ecModels) for various species, successfully enhancing chemical production. Building upon studies that allocate macromolecule resources, we developed a Python-based workflow (ECMpy) that constructs an enzyme-constrained model. This involves directly imposing an enzyme amount constraint in GEM and accounting for protein subunit composition in reactions. However, this procedure demands manual collection of enzyme kinetic parameter information and subunit composition details, making it rather user-unfriendly. In this work, we've enhanced the ECMpy toolbox to version 2.0, broadening its scope to automatically generate ecGEMs for a wider array of organisms. ECMpy 2.0 automates the retrieval of enzyme kinetic parameters and employs machine learning for predicting these parameters, which significantly enhances parameter coverage. Additionally, ECMpy 2.0 introduces common analytical and visualization features for ecModels, rendering computational results more user accessible. Furthermore, ECMpy 2.0 seamlessly integrates three published algorithms that exploit ecModels to uncover potential targets for metabolic engineering. ECMpy 2.0 is available at https://github.com/tibbdc/ECMpy or as a pip package (https://pypi.org/project/ECMpy/).

Abstract Background The rapid transmission and high pathogenicity of respiratory viruses significantly impact the health of both children and adults. Extracting and detecting their nucleic acid is crucial for disease prevention and treatment strategies. However, current extraction methods are laborious and time-consuming and show significant variations in nucleic acid content and purity among different kits, affecting detection sensitivity and efficiency. Our aim is to develop a novel method that reduces extraction time, simplifies operational steps, and ensures high-quality acquisition of respiratory viral nucleic acid. Methods We extracted respiratory syncytial virus (RSV) nucleic acid using reagents with different components and analyzed cycle threshold (Ct) values via quantitative real-time polymerase chain reaction (qRT-PCR) to optimize and validate the novel lysis and washing solution. The performance of this method was compared against magnetic bead, spin column, and precipitation methods for extracting nucleic acid from various respiratory viruses. The clinical utility of this method was confirmed by comparing it to the standard magnetic bead method for extracting clinical specimens of influenza A virus (IAV). Results The solution, composed of equal parts glycerin and ethanol (50% each), offers an innovative washing approach that achieved comparable efficacy to conventional methods in a single abbreviated cycle. When combined with our A Plus lysis solution, our novel five-minute nucleic acid extraction (FME) method for respiratory viruses yielded superior RNA concentrations and purity compared to traditional methods. FME, when used with a universal automatic nucleic acid extractor, demonstrated similar efficiency as various conventional methods in analyzing diverse concentrations of respiratory viruses. In detecting respiratory specimens from 525 patients suspected of IAV infection, the FME method showed an equivalent detection rate to the standard magnetic bead method, with a total coincidence rate of 95.43% and a kappa statistic of 0.901 (P < 0.001). Conclusions The FME developed in this study enables the rapid and efficient extraction of nucleic acid from respiratory samples, laying a crucial foundation for the implementation of expedited molecular diagnosis.

Abstract Abnormal trophoblast self-renewal and differentiation during early gestation is the major cause of miscarriage, yet the underlying regulatory mechanisms remain elusive. Here, we show that trophoblast specific deletion of Kat8, a MYST family histone acetyltransferase, leads to extraembryonic ectoderm abnormalities and embryonic lethality. Employing RNA-seq and CUT&Tag analyses on trophoblast stem cells (TSCs), we further discover that KAT8 regulates the transcriptional activation of the trophoblast stemness marker, CDX2, via acetylating H4K16. Remarkably, CDX2 overexpression partially rescues the defects arising from Kat8 knockout. Moreover, increasing H4K16ac via using deacetylase SIRT1 inhibitor, EX527, restores CDX2 levels and promoted placental development. Clinical analysis shows reduced KAT8, CDX2 and H4K16ac expression are associated with recurrent pregnancy loss (RPL). Trophoblast organoids derived from these patients exhibit impaired TSC self-renewal and growth, which are significantly ameliorated with EX527 treatment. These findings suggest the therapeutic potential of targeting the KAT8-H4K16ac-CDX2 axis for mitigating RPL, shedding light on early gestational abnormalities.

Abstract During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θcrit). Better quantification of θcrit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θcrit. We find an average global θcrit of 0.19 m3/m3, varying from 0.12 m3/m3 in arid ecosystems to 0.26 m3/m3 in humid ecosystems. θcrit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θcrit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θcrit, has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.

Proteins play a pivotal role in coordinating the functions of organisms, essentially governing their traits, as the dynamic arrangement of diverse amino acids leads to a multitude of folded configurations within peptide chains. Despite dynamic changes in amino acid composition of an individual protein (referred to as AAP) and great variance in protein expression levels under different conditions, our study, utilizing transcriptomics data from four model organisms uncovers surprising stability in the overall amino acid composition of the total cellular proteins (referred to as AACell). Although this value may vary between different species, we observed no significant differences among distinct strains of the same species. This indicates that organisms enforce system-level constraints to maintain a consistent AACell, even amid fluctuations in AAP and protein expression. Further exploration of this phenomenon promises insights into the intricate mechanisms orchestrating cellular protein expression and adaptation to varying environmental challenges.

Mutations in influenza virus neuraminidase (NA) can lead to viral resistance to NA inhibitors (NAIs). To update global influenza NA mutations and resistance to NAIs, we investigated epidemic information from global regions for NAIs-resistant influenza strains and analyzed their NA mutations. Drug-resistant mutations in NA, especially new mutations occurred in 2016-2024, were updated. The H274Y mutation in N1, a major contributor to NAI resistance, peaked in 2008, significantly impacting public health in countries like Japan and the USA. Three main mechanisms of NAI resistance were identified: catalytic site mutations, structural hindrance, and monomer stability changes. Although global resistance rates of H1N1pdm09, H3N2, and influenza B have remained stable at around 1%, sporadic emergence of resistant strains highlights the need for continued vigilance. The evolution of drug-resistant, transmissible strains through compensatory mutations underscores the urgency of new antiviral strategies. Strengthening global surveillance and adjusting public health policies, such as improving vaccine coverage and prudent antiviral use, remain essential to mitigating future risks.

Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer (BC) with a poor prognosis. Currently, chemotherapy and neoadjuvant chemotherapy continue to have limited efficacy in TNBC. With the deepening of research, nano targeted therapy shows a good application prospect in TNBC. Psoralen (PSO), an active component of Psoralea corylifolia, has significant advantages in inhibiting the growth of TNBC, but its poor solubility hampers its clinical practice. In this study, injectable psoralen polymer lipid nanoparticles (PSO-PLNs) were developed to deliver the hydrophobic drug to the target site and improve bioavailability. These nanoparticles were fully characterized in terms of morphology, particle size, surface zeta potential, encapsulation efficiency, drug loading, stability, and in vitro release profile. Besides, structural characteristics were determined by ultraviolet (UV) and infrared spectroscopy. Finally, in vivo pharmacokinetic studies of PSO-PLNs were performed in rats. The characteristic absorption of PSO and PSO-PLNs appeared in UV, indicating that PSO-PLNs had encapsulated PSO; there was no obvious characteristic absorption of PSO in infrared spectra, indicating that PSO was mostly encapsulated in the nano-shell. PSO-PLNs could maintain stable physicochemical properties for 1.5 months when stored at 4 °C. PSO-PLNs selectively released PSO at pH 6.5, and the sustained and controlled release effect was significantly different from that of PSO (p

Super-gravity field was reported to strongly intensify the buoyancy-driven flow of liquid during solidification, affecting the solute convection and morphology of eutectic structure in binary alloys. In ternary eutectic alloys, certain two-phase regions with a coarse structure can usually be detected concurrently along with three-phase eutectics, leading to the formation of heterogeneous structure with limited ductility. Currently, Al–Ce–Ni ternary eutectic alloy was chosen as a modal system, which was reported for the first time to be solidified under super-gravity field with high volume fraction of three-phase eutectics. Meanwhile, the formation of ultrafine-fibrous interconnected Al11Ce3–Al3Ni eutectic clusters with more “chains” and higher spatial connectivity was detected mainly due to the relatively higher nucleation rate. The high volume fraction and refinement of interconnected Al11Ce3–Al3Ni eutectic clusters with excellent thermal stability could contribute to enhancement of ductility and tensile strength at elevated-temperature. Interestingly, the strength retention at 300 °C and 400 °C were able to reach up to ∼68.1 % and ∼33.2 %, respectively.

Purpose: The limited understanding of long-term estradiol (E2) suppression poses challenges to the effectiveness of adjuvant therapy with aromatase inhibitors (AI), necessitating comprehensive serum E2 monitoring to address this issue. Therefore, our objective was to investigate serum E2 levels in women undergoing adjuvant AI treatment and evaluate the significance of such monitoring. Patients and methods: In this prospective cohort study, we recruited women who had received adjuvant AI treatment, including those who underwent ovarian function suppression (OFS). Serum E2 levels were measured using high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). The primary endpoint was the proportion of women with E2 levels exceeding 2.72 pg/mL, indicating inadequate suppression achieved with AI therapy. Results: A total of 706 patients were enrolled, including 482 women with OFS in combination with AI. Among them, 116 women (16.4 %) exhibited E2 levels exceeding 2.72 pg/mL. The majority of serum E2 elevations (77.6 %) occurred within the first two years of initiating endocrine therapy. Younger age, no prior chemotherapy, shorter duration of the current treatment regimen, and lower follicle stimulating hormone (FSH) levels were associated with inadequate E2 suppression. Serum E2 concentrations demonstrated dynamic variations and occasional rebound following adjuvant AI therapy. Conclusions: Despite receiving adjuvant AI treatment for nearly two years, a certain proportion of patients failed to achieve the adequate threshold of E2 suppression. Our findings emphasize the significance of monitoring serum E2 levels during adjuvant AI therapy, particularly within the first two years. Further research is imperative to facilitate a more comprehensive comprehension of E2 monitoring.

Background: To explore whether specific clinicopathological covariates are predictive for a benefit from capecitabine maintenance in early-stage triple-negative breast cancer (TNBC) in the SYSUCC-001 phase III clinical trial. Methods: Candidate covariates included age, menstrual status, type of surgery, postoperative chemotherapy regimen, Ki-67 percentage, histologic grade, primary tumor size, lymphovascular invasion, node status, and capecitabine medication. Their nonlinear effects were modeled by restricted cubic spline. The primary endpoint was disease-free survival (DFS). A survival prediction model was constructed using Cox proportional hazards regression analysis. Results: All 434 participants (306 in development cohort and 128 in validation cohort) were analyzed. The estimated 5-year DFS in development and validation cohorts were 77.8 % (95 % CI, 72.9%–82.7 %) and 78.2 % (95 % CI, 70.9%–85.5 %), respectively. Age and node status had significant nonlinear effects on DFS. The prediction model constructed using four covariates (node status, lymphovascular invasion, capecitabine maintenance, and age) demonstrated satisfactory calibration and fair discrimination ability, with C-index of 0.722 (95 % CI, 0.662–0.781) and 0.764 (95 % CI, 0.668–0.859) in development and validation cohorts, respectively. Moreover, patient classification was conducted according to their risk scores calculated using our model, in which, notable survival benefits were reported in low-risk subpopulations. An easy-to-use online calculator for predicting benefit of capecitabine maintenance was also designed. Conclusions: The evidence-based prediction model can be readily assessed at baseline, which might help decision making in clinical practice and optimize patient stratification, especially for those with low-risk, capecitabine maintenance might be a potential strategy in the early-disease setting.

Introduction: Common postoperative complications of total knee arthroplasty (TKA) include blood transfusion. Although risk factors and incidence of blood transfusion have been studied through national databases, the relative impact of each risk factor needs to be synthesized over a longer time period into a new model need to be revised. Material and methods: Patient data were extracted from the National Inpatient Sample (NIS), which is the largest hospital care database in the US, and analyse patient data retrospectively from 2010 through 2019. The final data included the patients undergoing TKA. The final analysis assessed the demographics of patients, type of insurance, type of hospital, length of stay (LOS), preoperative comorbidities, total charge, inpatient mortality, medical-surgical postoperative complications. Results: After extracting data from the NIS database, a total of 1,250,533 patients with TKA were included in the analysis, and the rate of transfusion was 6.60 %. TKA patients who receive blood transfusion had longer LOS (from 2-3 days to 3–4 days), more preoperative comorbidities, higher inpatient mortality rate, and increased total charge (P < 0.001). Moreover, postoperative complications associated with inpatients included sepsis, acute myocardial infarction and shock. Elective admission and private insurance were also regarded as protective factors. Conclusion: Blood transfusion could bring postoperative complications to patients, which were also linked to health costs and risks. It was also a common preoperative comorbidities for older patients who underwent TKA. Through better blood management strategies, we could reduce patient transfusion rates and improve clinical outcomes.Level of Evidence: Diagnostic Level Ⅲ.

The application of straw-degrading microbes (SDMs) with straw returned to the field is an effective measure to improve soil quality, increase yield, and maintain soil microorganisms. However, the utilization of SDMs in winter in north China is limited by the poor effects at low temperatures. This study investigated the effects of a new compound SDM, including a novel low-temperature fungus Pseudogymnoascus sp. SDF-LT, on winter wheat yield, soil improvement, and soil microbial diversity. A 2-year field experiment was conducted in two different soil textures of wheat–maize rotation fields with full corn straw return and application of SDMs at an amount of 67.5 kg hm−2. After 2 years of continuous application of SDMs, the winter wheat yield increased significantly, reaching 9419.40 kg hm−2 in Ningjin (NJSDM) and 9107.25 kg hm−2 in Mancheng (MCSDM). The soil properties have been significantly improved compared with the single straw return group, especially the sandy loam soil, whose quality is relatively low. The analysis of soil microbial diversity showed that SDMs significantly reduced the Chao1, Shannon, Simpson, and observed species of the sandy loam soil in the MCSDM group. The Simpson and Shannon indexes of fungi diversity in the two experimental sites were significantly increased by SDMs. The negative correlation of fungi increased from 47.1 to 48.85% in the SDM groups. The soil-dominant microbes changed in the SDM groups, in which the interactions between microbes were enhanced. These results suggested that the SDMs changed the the soil microbial community structure and its diversity and complexity, which is beneficial for crop growth. Our study provided sufficient evidence for the utilization of low-temperature SDMs with straw return in cold winter, which plays a role in soil improvement, especially for low-quality soils, to increase crop yield.

ObjectivesThis study aims to evaluate the efficacy of repeated transcranial magnetic stimulation (rTMS) combined with fluoxetine in enhancing the early antidepressant response in first-episode adolescent depression cases, providing insights for patient diagnosis and treatment.MethodsOne hundred and thirty-five adolescents experiencing their first depressive episode were randomly assigned to either a sham group treated with fluoxetine or to low or high repetitive transcranial magnetic stimulation (rTMS) groups receiving both rTMS and fluoxetine. Therapeutic effects were assessed by comparing changes in Hamilton Depression Scale (HAMD-17) scores, cognitive function scores from the Wisconsin Card Sorting Test (WCST), and Clinical Global Impression-improvement (CGI-I) scores, along with recording adverse reactions.ResultsThe total effectiveness rate in the rTMS groups (Low, 95.56%; High, 97.78%) was significantly higher than in the Sham rTMS group (80%) (F = 11.15, P

ObjectiveThis study aimed to distinguish between healthy controls and patients with OSAHS regarding homocysteine (HCY) levels and investigate how individuals with OSAHS respond to continuous positive airway pressure ventilation (CPAP) in terms of serum and plasma HCY levels.MethodsTo ascertain published articles about OSAHS, an exhaustive search was performed across medical databases, encompassing PubMed, Web of Science, EMBASE, CNKI, and Cochrane Library, until January 2, 2024. This study reviewed the literature regarding HCY levels in individuals with OSAHS and control groups, HCY levels under pre- and post-CPAP treatment, the Pearson/Spearman correlation coefficients between HCY levels and apnea-hypopnea index (AHI), and the hazard ratio (HR) of HCY levels concerning the occurrence of major adverse cerebrocardiovascular events (MACCEs) in patients with OSAHS. Meta-analyses were performed using weighted mean difference (WMD), correlation coefficients, and HR as effect variables. The statistical analysis was conducted using the R 4.1.2 and STATA 11.0 software packages.ResultsIn total, 33 articles were selected for the final analysis. The OSAHS group exhibited significantly higher serum/plasma HCY levels than the control group (WMD = 4.25 μmol/L, 95% CI: 2.60–5.91, P< 0.001), particularly among individuals with moderate and severe OSAHS. Additionally, subgroup analysis using mean age, ethnicity, mean body mass index, and study design type unveiled significantly elevated levels of HCY in the serum/plasma of the OSAHS group compared to the control group. CPAP treatment can significantly decrease serum/plasma HCY levels in patients with OSAHS. Moreover, elevated HCY levels in individuals with OSAHS could be one of the risk factors for MACCEs (adjusted HR = 1.68, 95% CI = 1.10–2.58, P = 0.017). AHI scores show a positive correlation with serum/plasma HCY levels.ConclusionPatients with OSAHS had elevated serum/plasma HCY levels compared to healthy controls; however, CPAP therapy dramatically decreased HCY levels in patients with OSAHS. In patients with OSAHS, elevated HCY levels were linked with an increased risk of MACCEs, and HCY was positively connected with AHI values. HCY levels may serve as a useful clinical indicator for determining the severity and efficacy of OSAHS treatments.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42024498806.

Abstract Dysfunction of invariant natural killer T (iNKT) cells contributes to immune resistance of tumors. Most mechanistic studies focus on their static functional status before or after activation, not considering motility as an important characteristic for antigen scanning and thus anti-tumor capability. Here we show via intravital imaging, that impaired motility of iNKT cells and their exclusion from tumors both contribute to the diminished anti-tumor iNKT cell response. Mechanistically, CD1d, expressed on macrophages, interferes with tumor infiltration of iNKT cells and iNKT-DC interactions but does not influence their intratumoral motility. VCAM1, expressed by cancer cells, restricts iNKT cell motility and inhibits their antigen scanning and activation by DCs via reducing CDC42 expression. Blocking VCAM1-CD49d signaling improves motility and activation of intratumoral iNKT cells, and consequently augments their anti-tumor function. Interference with macrophage-iNKT cell interactions further enhances the anti-tumor capability of iNKT cells. Thus, our findings provide a direction to enhance the efficacy of iNKT cell-based immunotherapy via motility regulation.

Abstract Background Seed endophytic bacteria are beneficial to plants. They improve seedling growth by enhancing plant nutrient uptake, modulating stress-related phytohormone production, and targeting pests and pathogens with antibiotics. Seed endophyte composition can be influenced by pollination, plant cultivar, and soil physicochemical conditions. However, the effects of plant community richness on seed endophytes are unknown. To investigate the effects of increasing plant species richness on the diversity and composition of the seed microbiome, we made use of a well-established long-term biodiversity experiment in Germany (The Jena Experiment). We sampled seeds from different Plantago lanceolata blossoms in a plant diversity gradient ranging from monoculture to 16 species mixtures. The seeds were surface sterilized to remove seed surface-associated bacteria and subjected to a metabarcoding approach to assess bacterial community structure. Results Our data indicate a very stable core microbiome, which accounted for more than 90% of the reads and was present in all seeds independent of the plant richness level the seeds originated from. It consisted mainly of reads linked to Pseudomonas rhizosphaerae, Sphingomonas faeni and Pirellulla spp. 9% of the obtained reads were not part of the core microbiome and were only present in plots of specific diversity levels. The number of unique ASVs was positively correlated with plant richness. Interestingly, most reads described as non-core members belonged to the same genera described as the core microbiome, indicating the presence of different strains or species with possibly different functional properties important for seed performance. Conclusion Our data indicate that Plantago lanceolata maintains a large seeds core microbiome across the plant richness gradient. However, the number of unique ASVs increases alongside the plant community richness, indicating that ecosystem biodiversity also mitigates diversity loss in seed endophytes.

With the rapid development of Artificial Intelligence (AI) technology in the art field, AI painting tools (AIPT) have attracted a high interest in the creation of painting art. However, the factors affecting Chinese users’ continued or interrupted use of AIPTs have not been adequately studied. This study builds a new theoretical model based on the perspective of user experience, combining the Expectation Confirmation Model (ECM) and the Technology Acceptance Model (TAM), with the aim of deeply exploring the Chinese users’ continuance intention to use AIPT in the painting process. We collected data from 532 Chinese users that regarded AIPT as a production tool and performed data analysis and model testing using SPSS 27 and Partial Least Squares Structural Equation Modeling (PLS-SEM) with Smartpls 4. The results of the study showed a positive trend in the overall continuous intention to use AIPT. Among the 14 hypotheses proposed, 11 were validated and 3 were rejected. The emotion experience (EE) has the most significant effect on users’ continuance intention (CI), with users valuing the emotional involvement in the AIPT experience. This is followed by satisfaction (SAT), attitude (ATT), perceived usefulness (PU), and perceived trust (PT), while perceived intelligence (PI) and perceived novelty (PN) indirectly affect CI through the mediating variables of PT and SAT. The findings of this study not only contribute both theoretical insights into the continued use of AIPT in the painting process, and a comprehensive and robust discussion of the future direction of AIPT. Furthermore, it offers valuable technical solutions and practical guidance for AIPT developers, underscoring the importance of considering user experience and emotional needs when optimizing technology. It also improves the sustained usage of AIPT in painting creation and facilitates the co-creation of both human beings and AI, which provides essential information for the further commercialization of the AI painting art field.

Abstract Background Magnesium (Mg) is both an essential macro-element and a known catalyst, and it plays a vital role in various physiological activities and mechanisms in relation to chronic kidney disease (CKD). However, epidemiological evidence involving this is limited and not entirely consistent. This study aims to explore the association of serum Mg concentrations with the risk of CKD among general Chinese adults. Methods A total of 8,277 Chinese adults were included in the wave of 2009 from the China Health and Nutrition Survey (CHNS). The primary outcome was the risk of CKD, which was defined as the estimated glomerular filtration rate (eGFR)

Water monitoring policies are recommended to ensure ecosystem preservation in industrial and agricultural development. Due to the reduction of water resources and the importance of sustainable rice production, it is necessary to develop relevant policies to promote the optimization of water and fertilizer distribution in rice paddy water environments. This article aims to plan the two objectives of water supply and reducing the environmental effects of nitrates in rice cultivation and analyzing the maximum and minimum benefits. By modifying the methods of fertilization and water distribution, the amount of production can be gradually increased by taking into account the harmful effects on the environment. Water and nitrate have a synergistic effect on the growth of paddy rice. However, the amount of runoff that is affected by nitrates is directly related to the pollution of aquatic environments. The results confirmed the correlation between nitrate concentration and production and reported the reduction of its negative effects depending on the management of inflow and outflow to rice fields. Changing the outflow according to the fertilization time and the inflow rate is an effective solution in the fertilizer nitrogen uptake and reducing the nitrate concentration in surface water sources in the long term. HIGHLIGHTS Achieving sustainability in the ecosystem and food security requires the development of research on the correlation between these factors and water resources.; The multi-objective model increased the sustainability of the ecosystem against pollutants by increasing benefits.;

Understanding housing preferences is critical for successful compact city development. However, there is limited research on understanding preference heterogeneity in dwelling type choices. Using the Household Income and Labour Dynamics in Australia survey, this paper identifies the key housing and built environment characteristics associated with changes in dwelling type choice from detached houses to high-density. A latent class choice model captures the heterogeneity of dwelling type preferences within a traditionally low-density city, Brisbane, Australia. Findings reveal six household classes with distinct dwelling preferences: Class 1 (senior households without children with other family members) and Class 2 (couple families with children) in inner-city areas, Class 3 (high-income young households) and Class 4 (low-income households without children) in middle-city areas, Class 5 (low-income families with children) and Class 6 (middle-income young families without children) in outer-city areas. Residential environments with better access to educational facilities encourage Classes 3 and 6 to change to high-density living. Greater land use diversity encourages Classes 2, 3, and 6 to move towards high-density living. The findings can be used to design and improve high-density housing for targeted population groups across inner-, middle- and outer-city areas.

ABSTRACTThe effects of microbial contamination on the rancidity of Huangjiu (Chinese rice wine) during pottery jar storage were studied. With the increase in the rancidity of Huangjiu, the alcohol content decreased, while the conductivity increased significantly. The sour taste and umami taste of Huangjiu increased, leading to flavor deterioration. Meanwhile, the increase in biogenic amine content makes Huangjiu unfit for drinking. The changes in components showed that the degree of rancidity was related to the metabolism of organic acids and amino acids caused by contaminated microorganisms. According to the analysis of microbial community structure, more microorganisms were found in the severe rancid Huangjiu. This indicated that with the aggravation of the degree of rancidity, the community structure of the contaminated microorganisms becomes complex, and potentially pathogenic microorganisms such as Arcobacter species were detected. Therefore, the change of components of Huangjiu will also affect the community structure of contaminated microorganisms.

Key Points The editors thank the 2023 peer reviewers

The purpose of the present study was to investigate the effects of different levels of a Chinese herbal medicine formulation combined with JM113 (CHM-JM113) on growth performance, antioxidant capacity, organ index, and intestinal health of AA broilers. The AA broiler chicks were randomly allocated to 5 treatments as follows: a basic diet for the control group, the basic diet supplemented with 0.25% CHM-JM113, 0.5% CHM-JM113, 1% CHM-JM113 and 2% CHM-JM113 for the treatment group, respectively. The results showed that the addition of CHM-JM113 to the diet significantly reduced the mortality (p 0.05). Comparing the control group, 0.5 and 1% CHM-JM113 group significantly improved the organ index of liver, spleen and bursa (p

BackgroundThe timely diagnosis of tuberculosis through innovative biomarkers that do not rely on sputum samples is a primary focus for strategies aimed at eradicating tuberculosis. miR-29 is an important regulator of tuberculosis pathogenesis. Its differential expression pattern in healthy, latent, and active people who develop tuberculosis has revealed its potential as a biomarker in recent studies. Therefore, a systematic review and meta-analysis were performed for the role of miR-29 in the diagnosis of tuberculosis.MethodsEMBASE, PubMed, CNKI, Web of Science, and Cochrane Library databases were searched utilizing predefined keywords for literature published from 2000 to February 2024.Included in the analysis were studies reporting on the accuracy of miR-29 in the diagnosis of tuberculosis, while articles assessing other small RNAs were not considered. All types of study designs, including case–control, cross-sectional, and cohort studies, were included, whether prospectively or retrospectively sampled, and the quality of included studies was determined utilizing the QUADAS-2 tool. Publication bias was analyzed via the construction of funnel plots. Heterogeneity among studies and summary results for specificity, sensitivity, and diagnostic odds ratio (DOR) are depicted in forest plots.ResultsA total of 227 studies were acquired from the various databases, and 18 articles were selected for quantitative analysis. These articles encompassed a total of 2,825 subjects, primarily sourced from the Asian region. Patient specimens, including sputum, peripheral blood mononuclear cells, cerebrospinal fluid and serum/plasma samples, were collected upon admission and during hospitalization for tuberculosis testing. miR-29a had an overall sensitivity of 82% (95% CI 77, 85%) and an overall specificity of 82% (95% CI 78, 86%) for detecting tuberculosis. DOR was 21 (95% CI 16–28), and the area under the curve was 0.89 (95% CI 0.86, 0.91). miR-29a had slightly different diagnostic efficacy in different specimens. miR-29a showed good performance in both the diagnosis of pulmonary tuberculosis and extrapulmonary tuberculosis. miR-29b and miR-29c also had a good performance in diagnosis of tuberculosis.ConclusionAs can be seen from the diagnostic performance of miR-29, miR-29 can be used as a potential biomarker for the rapid detection of tuberculosis.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=461107.

IntroductionRapid identification of infected individuals through viral RNA or antigen detection followed by effective personal isolation is usually the most effective way to prevent the spread of a newly emerging virus. Large-scale detection involves mass specimen collection and transportation. For biosafety reasons, denaturing viral transport medium has been extensively used during the SARS-CoV-2 pandemic. However, the high concentrations of guanidinium isothiocyanate (GITC) in such media have raised issues around sufficient GITC supply and laboratory safety. Moreover, there is a lack of denaturing transport media compatible with SARS-CoV-2 RNA and antigen detection.MethodsHere, we tested whether supplementing media containing low concentrations of GITC with ammonium sulfate (AS) would affect the throat-swab detection of SARS-CoV-2 or a viral inactivation assay targeting coronavirus and other enveloped and non-enveloped viruses. The effect of adding AS to the media on RNA stability and its compatibility with SARS-CoV-2 antigen detection were also tested.Results and discussionWe found that adding AS to the denaturing transport media reduced the need for high levels of GITC, improved SARS-COV-2 RNA detection without compromising virus inactivation, and enabled the denaturing transport media compatible with SARS-CoV-2 antigen detection.

In this study, we investigated the oxidative mechanisms of nano zero-valent iron (nZVI) enhanced potassium ferrate (K2FeO4), focusing on tributyltin (TBT) and triphenyltin (TPhT) as target pollutants. The addition of nZVI enhanced the degradation of both organic tin compounds by K2FeO4, exhibiting pseudo-first-order kinetics influenced by pH, carbonate, and fulvic acid. nZVI, as a reducing agent, facilitated the generation of stronger oxidizing species Fe (V) and Fe (IV) from K2FeO4 through electron transfer. The presence of hydroxyl radicals (OH) was confirmed by tert-butyl alcohol (TBA) verification. Intermediate products of TBT degradation by nZVI-enhanced K2FeO4 were identified using GC-MS, confirming de-alkylation leading to stepwise oxidation to inorganic tin ions. Due to excessively long Sn-C bonds in diphenyltin, rendering them unstable, Density Functional Theory (DFT) calculations were employed. Results indicated that Fe (IV) and Fe (V) predominantly attacked the Sn-C bonds of TPhT, while OH primarily targeted the benzene ring. HOMO energy levels suggested that Fe (V) was more prone to oxidizing TPhT than Fe (IV). Gibbs free energy calculations demonstrated that, in the presence of Fe (IV) and Fe (V), the energy barrier for breaking bonds and oxidizing into inorganic tin ions decreased, favoring the process over the self-decomposition of TPhT. Additionally, the lower energy barrier for OH indicated an easier degradation of TPhT. This study reveals that nZVI-enhanced K2FeO4 effectively removes TBT and TPhT, contributing to the understanding of the ferrate-mediated degradation mechanism of organic tin compounds. The findings offer insights and theoretical guidance for remediating organic tin pollution in aquatic environments.

This paper brings a comprehensive systematic review of the application of geospatial artificial intelligence (GeoAI) in quantitative human geography studies, including the subdomains of cultural, economic, political, historical, urban, population, social, health, rural, regional, tourism, behavioural, environmental and transport geography. In this extensive review, we obtain 14,537 papers from the Web of Science in the relevant fields and select 1516 papers that we identify as human geography studies using GeoAI via human scanning conducted by several research groups around the world. We outline the GeoAI applications in human geography by systematically summarising the number of publications over the years, empirical studies across countries, the categories of data sources used in GeoAI applications, and their modelling tasks across different subdomains. We find out that existing human geography studies have limited capacity to monitor complex human behaviour and examine the non-linear relationship between human behaviour and its potential drivers—such limits can be overcome by GeoAI models with the capacity to handle complexity. We elaborate on the current progress and status of GeoAI applications within each subdomain of human geography, point out the issues and challenges, as well as propose the directions and research opportunities for using GeoAI in future human geography studies in the context of sustainable and open science, generative AI, and quantum revolution.

BackgroundSarcopenia, marked by a reduction in skeletal muscle mass and function, is a condition that can manifest in elderly patients with cancer and has been recognized as a possible adverse factor affecting the survival of individuals diagnosed with malignant tumors. This systematic review and meta-analysis aimed to examine the prevalence of sarcopenia in individuals with cholangiocarcinoma while concurrently investigating the potential correlations between the presence of sarcopenia and various critical factors, including survival outcomes and postoperative complications.MethodsA comprehensive search was conducted across multiple databases, including EMBASE, PubMed, Web of Science, Cochrane Library, and CNKI, employing keywords such as sarcopenia, cholangiocarcinoma, and prognosis. This research explored the prognostic value of sarcopenia on the survival of cholangiocarcinoma. The findings of this meta-analysis were presented using forest plots and a summarized effects model. The Newcastle-Ottawa Scale (NOS) was employed to evaluate the quality of the studies included in the analysis.ResultsA total of 33 articles from five databases were in in the quantitative analysis. A comprehensive meta-analysis revealed that the overall prevalence of sarcopenia among individuals diagnosed with cholangiocarcinoma was43%. Moreover, the analysis revealed a significant and noteworthy correlation between sarcopenia and key clinical parameters such as overall survival (OS), Recurrence-Free Survival (RFS), and Disease-Free Survival (DFS) in patients with cholangiocarcinoma. Subgroup analysis revealed that, when categorized by various ethnicities, diagnostic techniques, and tumor locations, sarcopenia consistently retained its status as a negative predictive factor. Furthermore, sarcopenia has emerged as a risk factor for postoperative complications. All included studies had an NOS score greater than 5, indicating a high quality of evidence.ConclusionThe results suggest that sarcopenia is significantly related to survival outcomes and postoperative complications in cholangiocarcinoma. Appropriate diagnosis and treatment of sarcopenia should be implemented to improve the prognosis of individuals with cholangiocarcinoma.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023479866, identifier CRD42023479866.

The exploitation of water resources to provide water for agriculture follows methods that increase the efficiency of adopted policies. One of the effective ways to improve the efficiency of these systems is to evaluate the role of flow estimation in improving performance indicators such as reliability and vulnerability. In the correlation of water, energy and food, the purpose of decision-making is to achieve a balance between water extraction and energy consumption, which will lead to a reduction in the risk of supplying the water needed by the plant during periods of drought stress. In this article, a decision-making method using discrete wavelet transform and primal-dual algorithm is introduced to estimate the amount of monthly groundwater extraction. The proposed model has been evaluated by the Nash–Sutcliffe method and the mean squared error and optimized to increase the reliability of agricultural water supply. The results indicate the strong role of the accuracy of the proposed method in the efficiency of the aforementioned policies, as it has shown an 8% increase in reliability. HIGHLIGHT A decision-making method is proposed to estimate the amount of monthly groundwater exploitation.; Discrete wavelet transform model and primal-dual algorithm have been applied to evaluate solutions.;

Abstract Background Major depressive disorder (MDD) has a high incidence and an unknown mechanism. There are no objective and sensitive indicators for clinical diagnosis. Objective This study explored specific electrophysiological indicators and their role in the clinical diagnosis of MDD using machine learning. Methods Forty first-episode and drug-naïve patients with MDD and forty healthy controls (HCs) were recruited. EEG data were collected from all subjects in the resting state with eyes closed for 10 min. The severity of MDD was assessed by the Hamilton Depression Rating Scale (HAMD-17). Machine learning analysis was used to identify the patients with MDD. Results Compared to the HC group, the relative power of the low delta and theta bands was significantly higher in the right occipital region, and the relative power of the alpha band in the entire posterior occipital region was significantly lower in the MDD group. In the MDD group, the alpha band scalp functional connectivity was overall lower, while the scalp functional connectivity in the gamma band was significantly higher than that in the HC group. In the feature set of the relative power of the ROI in each band, the highest accuracy of 88.2% was achieved using the KNN classifier while using PCA feature selection. In the explanatory model using SHAP values, the top-ranking influence feature is the relative power of the alpha band in the left parietal region. Conclusions Our findings reveal that the abnormal EEG neural oscillations may reflect an imbalance of excitation, inhibition and hyperactivity in the cerebral cortex in first-episode and drug-naïve patients with MDD. The relative power of the alpha band in the left parietal region is expected to be an objective electrophysiological indicator of MDD.

ObjectiveTo examine the impact of extreme apparent temperature (AT) on daily emergency visits for hypertension in Shenzhen city, Guangdong province for providing evidence to revision of public health policies relevant to hypertension management and ambulances allocation. MethodsThe data on daily emergency visits for hypertension from January 2013 to December 2020 were collected from the Shenzhen First-Aid Service Platform and daily meteorological data of Shenzhen city over the same period were collected simultaneously for the estimation of daily average AT. Distributed lag nonlinear model (DLNM) was used to analyze the lag day and lag period effects of extreme AT on daily emergency visits for hypertension. Relative risk (RR) and population attributable risk percent (PARP%) were adopted in estimating the effects. ResultsDuring the 8-year period in the city, totally 14 491 outpatient emergency visits for hypertension occurred based on the records of the platform; the daily number of visits ranged from 1 to 28 and the average number of daily visits was 9.28 ± 0.90. During the same period for the city, the lowest daily average AT was – 4 ℃ and the highest was 39.4 ℃, with an average AT of 25.62 ± 7.95 ℃. A nonlinear effect of extreme AT on daily emergency visits for hypertension was observed; the number of the daily visits decreased with daily average AT but increased with daily average AT when the daily average AT being 30 ℃ and above. The results of DNLM analysis showed that in comparison to appropriate AT (30 ℃), both extreme low AT (9 ℃) and extreme high AT (36 ℃) were associated with an increased risk of daily emergency visit for hypertension during the lag period of 0 – 21 day, with the relative risk (RR) (95% confidence interval [95%CI]) of 1.783 (1.303 – 2.433) and 1.315 (0.994 – 1.747); the lag effect of the extreme low AT was much stronger on the daily emergency visits of male hypertension patients and those aged under 65 years, with the RR (95%CI) of 1.721 (1.050 – 2.811) and 1.872 (1.184 – 2.982), respectively. The PARP of extreme low AT-related daily emergency visits for hypertension was 13.64% generally for the study period. ConclusionThe extreme AT is of significant impact on daily emergency visit of hypertension patients in Shenzhen city, especially for the male patients and the patients aged under 65 years.

Abstract Background Opa interacting protein 5 (OIP5), which is a cancer/testis-specific gene, plays a cancer-promoting role in various types of human cancer. However, the role of OIP5 in the carcinogenesis and progression of ovarian cancer remains unknown. Methods We first analyzed the expression of OIP5 in ovarian cancer and various human tumors with the Sangerbox online analysis tool. GSE12470, GSE14407 and GSE54388 were downloaded from the Gene Expression Omnibus (GEO) database, and GEO2R was used to screen differentially expressed genes in ovarian cancer tissues. Gene Ontology (GO) enrichment analysis was used to explore the related biological processes. Receiver operating characteristic (ROC) curve was generated to evaluate the predictive ability of OIP5 for ovarian cancer. Next, RT–PCR, immunohistochemistry and Western blotting were utilized to evaluate the expression of OIP5 in ovarian cancer. CCK8, EdU proliferation assays and colony formation assays were used to measure cell proliferation, cell cycle progression was examined by PI staining and flow cytometry, and cell apoptosis was examined by Caspase3/7 activity assays. The effect of OIP5 on the migration and invasion of ovarian cancer cells was analyzed with Transwell assays. Results We found that OIP5 is highly expressed in ovarian cancer through bioinformatics analysis, and importantly, OIP5 may be an important biomarker for the prognosis and diagnosis of ovarian cancer. RT–PCR assays, immunohistochemistry and Western blotting were also used to confirm the high expression of OIP5 in ovarian cancer. Subsequently, we demonstrated that the proliferation and migration of the ovarian cancer cell line A2780 were significantly inhibited after OIP5 gene silencing, apoptosis was increased and cell cycle progression was arrested at the G1 phase. Conclusion This study indicated that OIP5 was highly expressed in ovarian cancer and that downregulation of OIP5 inhibited the proliferation, migration and invasion of ovarian cancer cells, induced cell cycle arrest and promoted cell apoptosis. Therefore, OIP5 may be an important biomarker for the early diagnosis and potential target for treatment of ovarian cancer.

Plant recognition of pathogen-associated molecular patterns (PAMPs) is pivotal in triggering immune responses, highlighting their potential as inducers of plant immunity. However, the number of PAMPs identified and applied in such contexts remains limited. In this study, we characterize a novel PAMP, designated Ss4368, which is derived from Scleromitrula shiraiana. Ss4368 is specifically distributed among a few fungal genera, including Botrytis, Monilinia, and Botryotinia. The transient expression of Ss4368 elicits cell death in a range of plant species. The signaling peptides, three conserved motifs, and cysteine residues (C46, C88, C112, C130, and C148) within Ss4368 are crucial for inducing robust cell death. Additionally, these signaling peptides are essential for the protein’s localization to the apoplast. The cell death induced by Ss4368 and its homologous protein, Bc4368, is independent of the SUPPRESSOR OF BIR1-1 (SOBIR1), BRI1-ASSOCIATED KINASE-1 (BAK1), and salicylic acid (SA) pathways. Furthermore, the immune responses triggered by Ss4368 and Bc4368 significantly enhance the resistance of Nicotiana benthamiana to Phytophthora capsici. Therefore, we propose that Ss4368, as a novel PAMP, holds the potential for developing strategies to enhance plant resistance against P. capsici.

Kudzu root (Puerariae lobatae Radix) is the tuberous root of Pueraria lobata, family Leguminosae. Kudzu root contains a variety of beneficial active ingredients such as puerarin, daidzin, daidzein, genistenin, 3′-hydroxy puerarin, β-sitosterol, stigmasterol, arachidic acid, and so on. Modern medical research shows that active ingredients in kudzu root are widely used clinically as raw materials for the treatment of hyperglycemia, non-alcoholic fatty liver disease, myocardial infarction, alcohol addiction, oxidative stress, inflammatory response, and retinal blockage due to their various pharmacological effects such as improving cardiovascular circulation, lowering blood lipids, lowering blood pressure, lowering blood sugar, being antipyretic, being estrogen-like, and relieving alcohol. China has rich resources of kudzu root, and active ingredients are usually extracted before it is made into a preparation, so whether the extraction and separation process is reasonable will directly affect the ease of preparation and the efficacy of the treatment. This paper reviews the process methods for the extraction and separation of active ingredients in kudzu root and its common pharmacological activities. The aim is to provide some references for readers to compare the advantages and disadvantages of various extraction and separation methods as well as understand the active ingredients and pharmacological activities of kudzu root.

With the increasing online exposure of urban public spaces, the new concept of “internet-famous sites” has emerged in China. Social media users are the main contributors to this new phenomenon. To fully understand social media users’ preferences in such kinds of public spaces, this article took 27 typical riverfront internet-famous sites (RIFSs) in Changsha City (China) as an example. Through social media platform selection, keyword research, text and image data extraction, visual and emotional symbol coding, and manual calculations of coding frequency, this study investigated social media users’ perception of RIFSs, especially on visual and emotional preferences. The online images and review comments were extracted from the popular Chinese social media platform “Xiaohongshu”. We found that (1) the popularity of each RIFS had a significant head effect and there were far more positive emotions than neutral and negative emotions in review comments. (2) RIFSs in Changsha were divided into five categories: commercial RIFSs, art exhibition RIFSs, historical and cultural RIFSs, ecological recreational RIFSs, and uncultivated RIFSs. Social media users had different visual focuses on each kind of RIFS. (3) Social media users provided specific reasons for their emotional preferences towards different types of RIFSs. This study can provide a new perspective on improving waterfront vitality and offer a targeted and attractive method for waterfront regeneration that is different from traditional methods.

In the midst of a rapidly evolving economic landscape, the global demand for oil is steadily escalating. This increased demand has fueled marine extraction and maritime transportation of oil, resulting in a consequential and uneven surge in maritime oil spills. Characterized by their abrupt onset, rapid pollution dissemination, prolonged harm, and challenges in short-term containment, oil spill accidents pose significant economic and environmental threats. Consequently, it is imperative to adopt effective and reliable methods for timely detection of oil spills to minimize the damage inflicted by such incidents. Leveraging the YOLO deep learning network, this paper introduces a methodology for the automated detection of oil spill targets. The experimental data pre-processing incorporated denoise, grayscale modification, and contrast boost. Subsequently, realistic radar oil spill images were employed as extensive training samples in the YOLOv8 network model. The trained detection model demonstrated rapid and precise identification of valid oil spill regions. Ultimately, the oil films within the identified spill regions were extracted utilizing the simulated annealing particle swarm optimization (SA-PSO) algorithm. The proposed method for offshore oil spill survey presented here can offer immediate and valid data support for regular patrols and emergency reaction efforts.

Abstract Background Hypothyroidism is a common disease in the US population. The impact of hypothyroidism on perioperative complications of total hip arthroplasty is poorly understood. To examine risk factors and hospitalization costs in patients with hypothyroidism after total hip arthroplasty (THA) using a large-scale sample national database. Methods A case–control study was performed based on the national inpatient sample database from 2005 to 2014. With the use of propensity scores, patients with hypothyroidism were matched in a 1:1 ratio to those without hypothyroidism by age, gender, race, Elixhauser Comorbidity Index (ECI), and insurance type. Patient demographics, postoperative complications, length of stay (LOS), and hospital costs were compared between matched cohorts. Short-term complication rates after THA were compared using multivariate logistic analysis. Results The proportion of patients with hypothyroidism receiving THA was 12.97%. Linear regression analysis yielded that patients with hypothyroidism receiving THA were more likely to have postoperative acute anemia (odds ratio = 1.15; 95% confidence interval = 1.12–1.18) and higher mean hospital costs compared to the non-hypothyroid cohort. Conclusions This present study demonstrates that hypothyroid patients undergoing THA have a higher risk of short-term complications. Furthermore, it significantly increased the total cost of hospitalization, which deserves more attention from orthopedic surgeons.

This study investigated the impact of basalt fiber on the microstructure, compressive strength, fracture properties, and drying shrinkage of alkali-activated slag (AAS) with varying silicate modulus (Ms) of activators. The AAS samples were characterized by using the SEM-EDS, FTIR, and TGA tests. The results showed that the corrosion behavior of basalt fiber differed in the alkaline solution depending on the Ms of the activator. When the Ms is 0, a brittle shell-like gel layer tended to form on the surface of the basalt fiber, resulting in the weak bonding between the basalt fiber and AAS matrix and limiting the reinforcing effect of basalt fiber. The mechanical and fracture properties can be effectively improved when the Ms of AAS was above 1, as the tight bonding between the basalt fiber and the AAS matrix enhanced the bridging effect of the basalt fiber. Additionally. the structure of the C-A-S-H in AAS can be improved with the added basalt fiber, especially with high Ms, which further facilitated the enhancement of the mechanical and fracture properties of AAS. Moreover, the effectiveness of basalt fiber in reducing the drying shrinkage of AAS was enhanced with increasing Ms.

Abstract Background In recent years, minimally invasive and non-invasive rejuvenation methods have been welcomed. PRP has been used widely for skin rejuvenation, but there are few studies on PRP for lip rejuvenation. Objective The objective of this study was to investigate the preliminary effects of PRP for lip rejuvenation. Methods Between October 2018 and April 2023, 15 participants with lip aging (1 male, 14 females; range 27–58 years) were treated with PRP. The follow-up time was 3 to 24months. After 3 to 6 times treatments, beauty seekers and experienced physicians jointly evaluated effectiveness of treatment. The assessment included improvements in the colour, wrinkles, and skin texture of the lips before and after treatment. Results According to the beauty seekers and Surgeons ’evaluation, the aging characteristics of the lips of the 15 beauty seekers have been improved to varying degrees. The most obvious improvement was that the color of the lips which became more vivid. There was no swelling, bruising, scar hyperplasia and other complications. A participant was evaluated using the VISIA skin detector. The patient’s lip color and discoloration improved after treatment. Of the 15 participants treated. 3 participants experienced mild pain or discomfort during the injection process. There was no swelling, bruising, scar hyperplasia and other complications. Conclusion The results of this study revealed promising evidence of PRP as an effective option on lip rejuvenation. However, large, multi-center, controlled, long term, pilot studies are required to confirm the preliminary results of our study.

Summary: Composite structures integrated with metasurfaces and nonlinear films have emerged as alternative candidates to enhance nonlinear response. The cooperative interaction between the two components is complicated. Herein, a split-ring resonator (SRR)-type metasurface was fabricated on a free-standing nanocrystal diamond (NCD) film utilizing electron beam lithography, electron beam evaporation, and a lift-off process. The terahertz (THz) radiation from the SRR-NCD under normal incidence originates from the high-order magnetic resonance of SRR because the NCD film cannot produce detectable THz radiation at this incident angle. As increasing the incident angle, the contribution of the THz radiation from the NCD film gradually increases until reaching 40° incident angle limitation. The results indicate that this angular-dependent THz radiation is induced by the interplay between the NCD film and SRR. This study offers a new approach to investigate nonlinear processes in composite structures.

IntroductionRecently, moral distress in pediatric nursing has gained academic attention, yet comprehensive literature reviews on this group are scarce.AimsThis study aims to offer a detailed overview of moral distress among pediatric nurses, focusing on understanding its characteristics, prevalence, underlying causes, and consequences on the quality of patient care.MethodsEmploying a scoping review approach as recommended by the Joanna Briggs Institute, this study will systematically search through PubMed, Scopus, Web of Science, APA PsycInfo, and CINAHL databases using specific search strategies. Titles, abstracts, and full texts will be independently screened by two reviewers according to the eligibility criteria. Relevant data will be extracted, categorized, and subjected to narrative synthesis to draw comprehensive insights.ConclusionThe anticipated findings of this study will shed light on the nature, frequency, and drivers of moral distress among pediatric nurses, along with its broader implications for healthcare practitioners, organizational practices, and patient care outcomes.

The microbiome-gut-brain axis (MGBA) plays a critical role in schizophrenia (SZ). However, the underlying mechanisms of the interactions among the gut microbiome, brain networks, and symptom severity in SZ patients remain largely unknown. Fecal samples, structural and functional magnetic resonance imaging (MRI) data, and Positive and Negative Syndrome Scale (PANSS) scores were collected from 38 SZ patients and 38 normal controls, respectively. The data of 16S rRNA gene sequencing were used to analyze the abundance of gut microbiome and the analysis of human brain networks was applied to compute the nodal properties of 90 brain regions. A total of 1,691,280 mediation models were constructed based on 261 gut bacterial, 810 nodal properties, and 4 PANSS scores in SZ patients. A strong correlation between the gut microbiome and brain networks (r = 0.89, false discovery rate (FDR) -corrected p

The riparian is a buffer zone between the river and human society, and improper land development will increase the ecological vulnerability of the river basin. Different evaluation methods for the ecological impact of development behavior will produce different value perception results, which in turn will affect the judgment and choice of decision-makers and the public. Based on the construction of an opportunity-cost-based monetary valuation method in the SEEA-EA (System of Environmental Economic Accounting-Ecosystem Accounting), this study took the riparian under the influence of the Xiaolangdi Project of the Yellow River from 1990 to 2020 as the research object, and evaluated the impact of land development decisions on ecosystem services under the superimposed influence of major projects, policies and socio-economic changes. The results show that: (1) The inclusion of opportunity costs can reduce the distortion of ecological value caused by economic factors and supply–demand state. In the case study, the opportunity cost of each 5-year accounting period in 30 years reduced the total accounting value respectively by 196.76, 25.88, 80.57, 84.33, 27.96, and 577.48 million yuan. (2) Opportunity cost can effectively reflect the ecological profit and loss caused by land transformation between different ecosystem types caused by decision-making in different periods. From 2015 to 2020, the opportunity cost of ecosystems was high when the total ecological land in the riparian increased, which reflected the drastic changes in land use during the decision-making period. (3) Opportunity costs are included in the monetary account as part of the “stock reduction”, which directly reflects the risk of ecological land reduction and structural change caused by development behavior. This mixed account of physical and monetary stocks can reflect both physical changes in ecosystem services and ecological risks, thereby improving stakeholders’ scientific understanding of the fluctuations in the value of ecosystem services caused by riparian land use.

Objective: Few studies have applied deep learning to the discriminative analysis of schizophrenia (SZ) patients using the fusional features of multimodal MRI data. Here, we proposed an integrated model combining a 3D convolutional neural network (CNN) with a 2D CNN to classify SZ patients. Method: Structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) data were acquired for 140 SZ patients and 205 normal controls. We computed structural connectivity (SC) from the sMRI data as well as functional connectivity (FC), amplitude of low-frequency fluctuation (ALFF), and regional homogeneity (ReHo) from the rs-fMRI data. The 3D images of T1, ReHo, and ALFF were used as the inputs for the 3D CNN model, while the SC and FC matrices were used as the inputs for the 2D CNN model. Moreover, we added squeeze and excitation blocks (SE-blocks) to each layer of the integrated model and used a support vector machine (SVM) to replace the softmax classifier. Results: The integrated model proposed in this study, using the fusional features of the T1 images, and the matrices of FC, showed the best performance. The use of the SE-blocks and SVM classifiers significantly improved the performance of the integrated model, in which the accuracy, sensitivity, specificity, area under the curve, and F1-score were 89.86%, 86.21%, 92.50%, 89.35%, and 87.72%, respectively. Conclusions: Our findings indicated that an integrated model combining 3D CNN with 2D CNN is a promising method to improve the classification performance of SZ patients and has potential for the clinical diagnosis of psychiatric diseases.