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Abstract Pesticides in surface freshwater primarily originate from their emissions in agricultural lands, potentially leading to violations of surface freshwater quality standards. To aid global regulatory agencies in effectively managing surface freshwater quality by estimating and controlling pesticide emission rates, this study proposes a hierarchical screening approach for countries and regions worldwide to select appropriate modeling tools. Hierarchical indicators are introduced to classify countries globally, considering their spatial distribution areas, pesticide emission conditions, and legislative systems. Consequently, different categories of countries are matched with suitable model groups, such as the standard model group for regulatory scenarios, the general model group for continental scenarios, and the advanced model group with high spatial resolution. Results indicated that a total of 193 countries worldwide were categorized into six country groups, of which 153, 34, and 6 countries were found to fit the standard, general, and advanced model groups, respectively, based on the model assignments for these country groups. Furthermore, 12 commonly used pesticides were selected to demonstrate the back-calculation process, which estimates the pesticide emission rate (input) by pesticide surface freshwater quality standards (output) by standard and general model groups. The Advanced model group was not applied in this process due to its intensive computation. An approximate approach was developed to simplify the calculation of the emission rate factor of pesticides using the PWC and TOXSWA selected in the standard model group as well as SWAT in the general model group, serving as a demonstration. This approach can be applied to control pesticide emission rates from surface freshwater quality standards across countries that fit in the standard and general model groups. The results highlight that pesticide fate models selected through the hierarchical screening approach, can assist global countries in establishing a quantitative relationship between pesticide emission rates and surface freshwater quality standards, which can help global agencies manage pesticide emissions and freshwater quality from a legal perspective. There is a need to update and simplify suitable advanced model for calculation demonstration in future studies to aid in pesticide management. Further research is needed to thoroughly investigate pesticide emissions and freshwater residue concentrations under varying conditions.

Abstract Objective To report a new case of gastroblastoma and conduct an exhaustive review of the clinical, morphological, immunohistochemical, molecular features, diagnosis, treatment, and prognosis, to enhance understanding of this condition. Methods We retrospectively analyzed the case of a 50-year-old woman diagnosed with gastroblastoma and conducted a review and summary of relevant literature. Results To date, 27 cases have been reported, including the present case. The mean patient age at the time of presentation was 35.0 years (range, 5–74 years), and the disease showed no sex predilection. The most common location was the gastric antrum, and the average lesions size was 5.7 cm (range, 1.3–15 cm). Most patients underwent gastrectomy(n = 23), while several underwent ESD(n = 2) or EFTR(n = 1). Fusion genes were identified, including MALAT1–GLI1(n = 8), EWSR1-CTBP1(n = 1), PTCH1:GLI2(n = 1), and ACTB-GLI1(n = 1)Four patients had metastasis and one of them dead of disease. Immunohistochemical (IHC) analysis revealed that pancytokeratin was always positive in epithelioid components, while vimentin and CD10 were always positive in mesenchymal components. CD56 were often positive in both two components. Conclusion A comprehensive evaluation of clinical and pathological features is crucial for accurate diagnosis. Partial gastrectomy and EFTR could be an appropriate treatment. The risk factors that affect the prognosis need more cases to be clearly defined. We present this exhaustive literature review to increase awareness of gastroblastoma, better characterize the disease, and provide a reference point for gastroblastoma research in the future.

Abstract Double-layer island working face main roadway coal pillars are affected by complex mining stress superposition, when different coal pillar width combinations, the surrounding rock stress field will produce different degrees of regional loading increase effect; the study of the surrounding rock stress field regional superposition loading increase law is meaningful to explaining the failure mode of the roadway and determining the critical control area. This study combines numerical simulation with on-site monitoring and other methods and draws the following conclusions: The superimposed loading increase law (“decreasing” → “increasing”) of the abutment pressure and deviatoric stress in the lower coal seam of the double-layer island working face during the mining; the type of the principal stress deflection in the advance working face region; and by obtaining the three types of development morphology of the deviatoric stress peak zone of the roadway and its corresponding nine evolution modes (one type of circular tube → four types of inverse hyperbolic body → four types of hyperbolic body) in the double-layered island working face mining. Indicated the critical reinforcement area corresponding to the main roadway when at different combinations of coal pillar widths; determined the main track roadway protective coal pillars width for 40 m and the shape of the roadway peak deviatoric stress zone is the inverse class hyperbolic body mode; according to the evolution mode of the peak deviatoric stress zone, determined the synergistic failure control program for the asymmetric critical zone of the roadway surrounding rock which is a targeted scientific support method; after the feedback of on-site monitoring and, the support program is reasonable and effective.

In order to evaluate the working condition of swivel flange under high temperature and high pressure more accurately, based on the swivel flange in existing pressure level (300~900 lb), the structure and model of the 1 500 lb and 2 500 lb swivel flange were constructed, and the strength and stiffness of the model were checked. Meanwhile, the finite element static mechanical analysis was carried out by using ABAQUS software. The results show that the calculated stress of the swivel flange under each nominal diameter is less than the allowable stress, and the stiffness meets the requirements. The pressure grade and the flange dimension have certain influence on the stress distribution of the swivel flange, and there are two stress concentration areas in the 1 500 lb swivel flange, which are the high neck of the small end of the hub and the contact area between the gaskets and the flange; In addition to the above two stress concentration areas, the 2 500 lb swivel flange also has stress concentration at the edge of the hub's step. The maximum stress always occurs at the high neck of the small end of the hub, and the maximum stress is less than the allowable stress of the material, so the designed high-pound swivel flange meets the usage requirement. The results of the study further enrich the structural design cases of 2 500 lb swivel flange, and provide some reference for the structure design of high-pound swivel flange.

Abstract Purpose Previous studies have suggested that obesity defined by body mass index(BMI) is a protective factor for bone mineral density(BMD), but have overlooked the potential influence of different types of obesity. This study aims to evaluate the correlation between abdominal obesity index A Body Shape Index(ABSI) and adolescent bone density, and analyze the relationship between abdominal obesity and bone metabolism. Methods A total of 1557 adolescent participants were included in NHANES from 2007 to 2018. Calculate the ABSI using a specific formula that takes into account waist circumference and BMI. A weighted multiple linear regression model is used to evaluate the linear correlation between ABSI and BMD. Forest plots are used to analyze the correlations between subgroups, and cubic splines are limited to evaluate the nonlinear correlations and saturation effects between ABSI and BMD. Results After adjusting for confounding factors, there was a significant linear correlation (P

Background: Rectal cancer (RC) is one of the most common types of cancer worldwide. With the development of artificial intelligence (AI), the application of AI in preoperative evaluation and follow-up treatment of RC based on magnetic resonance imaging (MRI) has been the focus of research in this field. This review was conducted to develop comprehensive insight into the current research progress, hotspots, and future trends in AI based on MRI in RC, which remains to be studied. Methods: Literature related to AI based on MRI and RC, as of November 2023, was obtained from the Web of Science Core Collection database. Visualization and bibliometric analyses of publication quantity and content were conducted to explore temporal trends, spatial distribution, collaborative networks, influential articles, keyword co-occurrence, and research directions. Results: A total of 177 papers (152 original articles and 25 reviews) were identified from 24 countries/regions, 351 institutions, and 81 journals. Since 2019, the number of studies on this topic has rapidly increased. China and the United States have contributed the highest number of publications and institutions, cultivating the most intimate collaborative relationship. The highest number of articles derive from Sun Yat-sen University, while Frontiers in Oncology has published the highest number of relevant articles. Research on MRI-based AI in this field has mainly focused on preoperative diagnosis and prediction of treatment efficacy and prognosis. Conclusions: This study provides an objective and comprehensive overview of the publications on MRI-based AI in RC and identifies the present research landscape, hotspots, and prospective trends in this field, which can provide valuable guidance for scholars worldwide.

Background: Sarcopenic obesity (SO) and osteoarthritis (OA) are highly prevalent musculoskeletal conditions that significantly impair health-related quality of life. Aim: This study investigated the association between SO and OA, and explored the potential mediating role of insulin resistance in this relationship. We utilized data from the National Health and Nutrition Examination Survey (NHANES) 1999–2018. Methods: This cross-sectional analysis employs NHANES data collected from 1999 to 2018, including participants aged 18 years and older. SO was assessed using dual-energy X-ray absorptiometry (DXA) measurements. Insulin resistance was estimated using the triglyceride-glucose (TyG) index. OA status was based on self-reported physician diagnosis. Statistical analyses included weighted logistic regression, restricted cubic spline (RCS) interaction analysis, mediation analysis using structural equation modeling (SEM), and receiver operating characteristic (ROC) curve analysis. Subgroup analyses were conducted based on age, sex, and diabetes status. Results: The sarcopenic obese group demonstrated the highest prevalence of OA (23.4 %), hypertension (47.8 %), and diabetes (12.0 %). Additionally, they exhibited elevated levels of triglycerides, cholesterol, glucose, blood urea nitrogen (BUN), creatinine, and uric acid. Logistic regression revealed significant positive associations between sarcopenic obesity, the TyG index, and OA risk. RCS analysis identified significant non-linear relationships and interactions of the TyG index with age, sex, and diabetes status on OA risk. Mediation analysis indicated that the TyG index mediated approximately 4.9 % of the effect of sarcopenic obesity on OA risk. ROC curve analysis demonstrated moderate diagnostic accuracy for the TyG index (AUC = 0.65), which improved when incorporated into the multivariate model (AUC = 0.78). Subgroup analyses confirmed significant associations between the TyG index and sarcopenic obesity with OA risk across different age, sex, and diabetes status categories. Conclusion: Our findings suggest a significant correlation between insulin resistance, as measured by the TyG index, and elevated OA risk in individuals with sarcopenic obesity. Targeting insulin resistance through future research may be a promising avenue to lower OA risk in this population.

Abstract The Early Cenozoic sedimentary archives of Tibet are crucial for elucidating the geodynamic processes related to continental collision, particularly crustal deformation and shortening. However, the lack of a reliable chronostratigraphic framework for the Cenozoic sedimentary basins in central Tibet has hindered a comprehensive understanding of the influence of the continuous India‐Asia convergence process on the tectonic evolution of the Tibetan hinterland. Here, we report new magnetostratigraphic ages and paleomagnetic results for the Niubao Formation exposed in the northern bank of the Siling Co. Positive field tests and microscopic observations suggest that the remanence is primary. We determine that the depositional age of the measured section was between 59.2 and 48.6 Ma. Our results reveal that the paleogeographic location of the Bangong‐Nujiang Suture Zone during the Late Paleocene–Early Eocene was 25.4 ± 2.1°N, thus supporting the model of two‐stage collision between India and Asia.

The study of extrachromosomal DNA (ecDNA), an element existing beyond classical chromosomes, contributes to creating a more comprehensive map of the cancer genome. In hematological malignancies, research on ecDNA has lacked comprehensive investigation into its frequency, structure, function, and mechanisms of formation. We re-analyzed WGS data from 208 hematological cancer samples across 11 types, focusing on ecDNA characteristics. Amplification of ecDNA was observed in 7 of these cancer types, with no instances found in normal blood cells. Patients with leukemia carrying ecDNA showed a low induction therapy remission rate (

In order to study the fracture position and engineering significance of the main roof plate structure under the condition of goaf on both sides (coal pillars), the double plasticized foundation boundary mechanical model of the main roof plate structure considering the elastic-plastic deformation of coal and the width and support capacity weakening of coal pillar on both sides is constructed. Based on the finite difference algorithm and the principal moment breaking criterion, the shape characteristics, location attributes and overall position characteristics of the main roof fault line above the asymmetric coal pillars area and the long side solid coal area are systematically calculated, and the new conclusions and important engineering significance of the new model are clarified by comparing with the traditional models from seven levels and four pairs of areas in transverse and longitudinal directions. The conclusions are as follows: ① The asymmetric coal pillars parameters on both sides have little influence on the main roof principal bending moment and fracture position above the long side solid coal area, but significantly affect the principal bending moment, position and fracture shape of the main roof above the coal pillar areas respectively. There are three types of evolution patterns of the main roof fracture line above the coal pillar areas on both sides (strong/wide coal pillar area + weak/narrow coal pillar area). With the increase of main roof thickness and elastic modulus, while coal pillars width, coal pillar bearing capacity and working face span decrease, its evolution law is as follows: asymmetric “continuous single arc + continuous single arc”→ “continuous single arc + open discontinuous double short arc”→ asymmetric “open discontinuous double short arc + open discontinuous double short arc”. ② The fracture line of the main roof above the long side solid coal area mainly has three types of location attributes. With the increase of main roof thickness and elastic modulus, while the plastic zone width and plasticization degree of solid coal and working face span decrease, its evolution law is as follows: the fracture line is above the plastic coal area (C-S type) → elastoplastic coal boundary area (C-TS type) → elastic coal area (C-T type). ③ With the increase of coal pillars width, coal pillar bearing capacity and working face span decrease, and considering the location attribute of the fracture line, the fracture mode and evolution law of the whole area of the main roof are as follows: the mode of C-S ()→the mode of C-TS ()→the mode of C-T ()→ mode of C-T ()→the mode of C-T (). Aiming at the three kinds of mechanical models for studying the fracture of the main roof plate structure with goaf (coal pillar) on both sides, the important differences of the three kinds of models are compared from seven levels, and its important engineering role is expounded from four transverse areas (front and rear of the mining area, coal pillar areas on both sides) and four longitudinal areas (asymmetric left coal pillar underlying and underlying mining space output/input coal pillar/body).

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been significantly alleviated. However, long-term health effects and prevention strategy remain unresolved. Thus, it is essential to explore the pathophysiological mechanisms and intervention for SARS-CoV-2 infection. Emerging research indicates a link between COVID-19 and bile acids, traditionally known for facilitating dietary fat absorption. The bile acid ursodeoxycholic acid potentially protects against SARS-CoV-2 infection by inhibiting the farnesoid X receptor, a bile acid nuclear receptor. The activation of G-protein-coupled bile acid receptor, another membrane receptor for bile acids, has also been found to regulate the expression of angiotensin-converting enzyme 2, the receptor through which the virus enters human cells. Here, we review the latest basic and clinical evidence linking bile acids to SARS-CoV-2, and reveal their complicated pathophysiological mechanisms.

Objective The different cutting mode of robot‐assisted TKAs may influence the accuracy of alignment. The purpose of this study was to compare alignment accuracy and early clinical outcomes between a CT‐based, saw cutting robotic system (MAKO) and a CT‐free, jig‐guided robotic system (ROSA) for total knee arthroplasty (TKA). Methods A total of 20 MAKO TKAs and 20 ROSA TKAs from June 2021 to June 2022 were retrospectively analyzed. Differences in the postoperative hip‐knee‐ankle (HKA) angle, lateral distal femoral angle (LDFA), medial proximal tibial angle (MPTA), posterior tibial slope (PTS) and 3° outlier frequency of the HKA, LDFA, MPTA and PTS were studied at 3 months and 1 year of follow‐up. The operative time and total blood loss (TBL) were compared between these two groups. Clinical outcomes at 1 year after surgery, including range of motion (ROM), Western Ontario McMaster University Osteoarthritis Index (WOMAC) score, and Knee Society Score‐2011 (KSS‐2011), were also compared between these two groups. Results The baseline characteristics of the two groups were comparable. There were no significant differences in the mean deviations of postoperative HKA, LDFA, MPTA or PTS between the two groups at 3 months or 1 year (all ps > 0.05). Moreover, there was no significant difference in the percentage of 3° outliers for HKA, LDFA, MPTA, or PTS between the two groups at 3‐month or 1‐year follow‐up (all ps > 0.05). The mean operation time of MAKO was longer than that of ROSA (112.7 ± 12.8 min vs 94.8 ± 23.0 min, p = 0.001), but the mean TBL (1356.7 ± 648.5 mL vs 1384.5 ± 676.3 mL) and transfusion rate (15.0% vs 5.0%) were not significantly different between the two groups (all ps > 0.05). No significant differences were found in postoperative ROM, WOMAC score or KSS score at 1 year (all ps > 0.05). Conclusion The MAKO and ROSA had similar accuracy and precision in TKA alignment. The clinical outcomes at 1 year after surgery were also comparable.

Abstract Purpose In VATS surgery, precise preoperative localization is particularly crucial when dealing with small-diameter pulmonary nodules located deep within the lung parenchyma. The purpose of this study was to compare the efficacy and safety of laser guidance and freehand hook-wire for CT-guided preoperative localization of pulmonary nodules. Methods This retrospective study was conducted on 164 patients who received either laser guidance or freehand hook-wire localization prior to Uni-port VATS from September 1st, 2022 to September 30th, 2023 at The First Affiliated Hospital of Soochow University. Patients were divided into laser guidance group and freehand group based on which technology was used. Preoperative localization data from all patients were compiled. The localization success and complication rates associated with the two groups were compared. The risk factors for common complications were analyzed. Results The average time of the localization duration in the laser guidance group was shorter than the freehand group (p

Abstract Chisel pick is a basic and important rock cutting tool, and the performance of chisel pick directly affects rock mining. In this paper, a rock cutting device was developed for chisel picks cutting experiments. The influence of the depth of cutting, width of chisel pick, rake angle, back clearance angle and tip fillet radius on the cutting performance such as cutting force, normal force, and specific energy has been comprehensively studied. In addition to the general conclusions, the experimental results show that the back clearance angle has an influence range on the cutting, and the ratio of the normal force to the cutting force decreases with the increase of the rake angle; the tip fillet radius greatly improve the mean cutting force and specific energy. The experimental results will provide data support for the design of chisel picks on rock excavation machinery and a more reasonable chisel pick cutting rock mechanics model.

AimClarify the potential diagnostic value of tongue images for coronary artery disease (CAD), develop a CAD diagnostic model that enhances performance by incorporating tongue image inputs, and provide more reliable evidence for the clinical diagnosis of CAD, offering new biological characterization evidence.MethodsWe recruited 684 patients from four hospitals in China for a cross-sectional study, collecting their baseline information and standardized tongue images to train and validate our CAD diagnostic algorithm. We used DeepLabV3 + for segmentation of the tongue body and employed Resnet-18, pretrained on ImageNet, to extract features from the tongue images. We applied DT (Decision Trees), RF (Random Forest), LR (Logistic Regression), SVM (Support Vector Machine), and XGBoost models, developing CAD diagnostic models with inputs of risk factors alone and then with the additional inclusion of tongue image features. We compared the diagnostic performance of different algorithms using accuracy, precision, recall, F1-score, AUPR, and AUC.ResultsWe classified patients with CAD using tongue images and found that this classification criterion was effective (ACC = 0.670, AUC = 0.690, Recall = 0.666). After comparing algorithms such as Decision Tree (DT), Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and XGBoost, we ultimately chose XGBoost to develop the CAD diagnosis algorithm. The performance of the CAD diagnosis algorithm developed solely based on risk factors was ACC = 0.730, Precision = 0.811, AUC = 0.763. When tongue features were integrated, the performance of the CAD diagnosis algorithm improved to ACC = 0.760, Precision = 0.773, AUC = 0.786, Recall = 0.850, indicating an enhancement in performance.ConclusionThe use of tongue images in the diagnosis of CAD is feasible, and the inclusion of these features can enhance the performance of existing CAD diagnosis algorithms. We have customized this novel CAD diagnosis algorithm, which offers the advantages of being noninvasive, simple, and cost-effective. It is suitable for large-scale screening of CAD among hypertensive populations. Tongue image features may emerge as potential biomarkers and new risk indicators for CAD.

In an effort to mitigate anthropogenic climate impacts the U.S. has established ambitious Nationally Determined Contribution (NDC) targets, aiming to reduce greenhouse gas emissions by 50% before 2030 and achieving net-zero emissions by 2050. Enhanced rock weathering (ERW)—the artificial enhancement of chemical weathering of rocks to accelerate atmospheric CO2 capture—is now widely seen as a potentially promising carbon dioxide removal (CDR) strategy that could help to achieve U.S. climate goals. Grinding rocks to smaller particle size, which can help to facilitate more rapid and efficient CO2 removal, is the most energy-demanding and cost-intensive step in the ERW life cycle. As a result, accurate life cycle analysis of ERW requires regional constraints on the factors influencing the energetic and economic demands of feedstock grinding for ERW. Here, we perform a state-level geospatial analysis to quantify how carbon footprints, costs, and energy demands vary among regions of the coterminous U.S. in relation to particle size and regional electricity mix. We find that CO2 emissions from the grinding process are regionally variable but relatively small compared to the CDR potential of ERW, with national averages ranging between ~5–35 kgCO2 trock−1 for modal particle sizes between ~10–100 μm. The energy cost for feedstock grinding also varies regionally but is relatively small, with national average costs for grinding of roughly 0.95–5.81 $ trock−1 using grid mix power and 1.35–8.26 $ trock−1 (levelized) for solar PV for the same particle size range. Overall energy requirements for grinding are also modest, with the demand for grinding 1 Gt of feedstock representing less than 2% of annual national electricity supply. In addition, both cost and overall energy demand are projected to decline over time. These results suggest that incorporating feedstock grinding into ERW deployment at scale in the coterminous U.S. should generally have only modest impacts on lifecycle emissions, cost-effectiveness, and energy efficiency.

Abstract High‐energy blue light is highly detrimental to health as it can penetrate the lens into the retina, potentially causing atrophy or even death of retinal pigment epithelial cells. To prevent the harmful effects of high‐energy blue light on our health, here the preparation of a photoconversion film specifically designed to block high‐energy blue light is reported, which is composed of green‐emissive carbon dots (G‐CDs) with a high photoluminescence quantum yield (PLQY = 95%) dispersed in polyvinyl alcohol (PVA) matrix. Notably, such a film (named as G‐CDs@PVA) not only converts an incident laser light with a short wavelength into a fluorescence with a longer wavelength, but also exhibits concentration‐dependent (0, 10, 20, and 30 wt.%) blue light barrier rate and green‐emissive intensity. With the increase of the concentration of G‐CDs in the film, the blue light barrier rate of the film as well as the maximum intensity of the green emission are also increased. When the concentration of G‐CDs reaches 30 wt.%, the blue light barrier rate of G‐CDs@PVA achieves up to 97%. Furthermore, G‐CDs@PVA film is attached to a blue light‐emitting diode (LED) chip to explore its practical application in the field of blocking blue light damage.

In order to improve the wear resistance and service life of mining sprockets, 40CrNiMoA sprockets cast by centrifugal electroslag casting were selected as the base material to study the effects of heat treatment processes on microstructure and mechanical properties of the alloy. The effects of different heat treatment processes on the mechanical properties of the steel, such as microhardness, friction and wear, and tensile strength were investigated with the orthogonal experiment method.The test results were analyzed by range analysis and comprehensive weighted scoring calculation to obtain the optimal heat treatment process parameters. Finally, experimental verification was conducted. The results show that the optimal heat treatment process obtained by the orthogonal test method is quenching at 880 ℃ for 0 .5 hours and high-temperature tempering at 600 ℃ for 2 hours. The microstructure of the sample after heat treatment is mainly tempered sorbite, with a Vickers hardness of 364 HV, a tensile strength of 1 166 MPa, and a wear rate of 0 .427×10-4 mm3/（N·m）. The validation test results are similar to the orthogonal experimental analysis, and the sample performance after heat treatment can meet the usage requirements. Therefore, the research results can provide a theoretical basis for the heat treatment process of mining sprocket parts, and are of great significance for effectively solving the wear resistance and service life of sprockets.

Defect detection in transparent materials typically relies on specific lighting conditions. However, through our work on defect detection for aircraft glass canopies, we found that using a single lighting condition often led to missed or false detections. This limitation arises from the optical properties of transparent materials, where certain defects only become sufficiently visible under specific lighting angles. To address this issue, we developed a dual-modal illumination system that integrates both forward and backward lighting to capture defect images. Additionally, we introduced the first dual-modal dataset for defect detection in aircraft glass canopies. Furthermore, we proposed an attention-based dual-branch modal fusion network (ADMF-Net) to enhance the detection process. Experimental results show that our system and model significantly improve the detection performance, with the dual-modal approach increasing the mAP by 5.6% over the single-modal baseline, achieving a mAP of 98.4%. Our research also provides valuable insights for defect detection in other transparent materials.

Hepatocellular carcinoma (HCC) ranks among the most prevalent malignant tumors, exhibiting a high incidence rate that presents a substantial threat to human health. The use of sorafenib and lenvatinib, commonly employed as single-agent targeted inhibitors, complicates the treatment process due to the absence of definitive targeting. Nevertheless, the advent of nanotechnology has injected new optimism into the domain of liver cancer therapy. Nanocarriers equipped with active targeting or passive targeting mechanisms have demonstrated the capability to deliver drugs to tumor cells with high efficiency. This approach not only facilitates precise delivery to the affected site but also enables targeted drug release, thereby enhancing therapeutic efficacy. As medical technology progresses, there is an increasing call for innovative treatment modalities, including novel chemotherapeutic agents, gene therapy, phototherapy, immunotherapy, and combinatorial treatments for HCC. These emerging therapies are anticipated to yield improved clinical outcomes for patients, while minimizing systemic toxicity and adverse effects. Consequently, the application of nanotechnology is poised to significantly improve HCC treatment. This review focused on targeted strategies for HCC and the application of nanotechnology in this area.

Bacterial infections and their increasing resistance to antibiotics pose a significant challenge in medical treatment. This study presents the synthesis and characterization of novel carbon dots (CDs) using levofloxacin (Lf), curcumin (Cur), and tea polyphenols (TP) through a facile hydrothermal method. The synthesized curcumin-tea polyphenol@carbon dots (Cur-TP@CDs) and levofloxacin-tea polyphenol@carbon dots (Lf-TP@CDs) were characterized using transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy, confirming their unique structural and chemical properties. Cur-TP@CDs exhibited an average particle size of 1.32 nanometers (nm), while Lf-TP@CDs averaged 1.58 nm. Both types demonstrated significant antibacterial activity, with Lf-TP@CDs showing superior effectiveness against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) in broth dilution and disc diffusion assays. Biofilm inhibition assays revealed a significant reduction in biofilm formation at higher concentrations. The ultraviolet-visible (UV-vis) and photoluminescence (PL) spectral analyses indicated efficient photon emission, and electron paramagnetic resonance (EPR) analysis showed increased singlet oxygen generation, enhancing bactericidal effects. Live and dead bacterial staining followed by scanning electron microscopy (SEM) analysis confirmed dose-dependent bacterial cell damage and morphological deformities. These findings suggest that Cur-TP@CDs and Lf-TP@CDs are promising antibacterial agents, potentially offering a novel approach to combat antibiotic-resistant bacterial infections.

Abstract Electrocatalytic CO2‐to‐formate conversion is considered an economically viable process. In general, Zn‐based nanomaterials are well‐known to be highly efficient electrocatalysts for the conversion of CO2 to CO, but seldom do they exhibit excellent selectivity toward formate. In this article, we demonstrate that a heterointerface catalyst ZnO/ZnSnO3 with nanosheet morphology shows enhanced selectivity with a maximum Faradaic efficiency (FE) of 86% at −0.9 V versus reversible hydrogen electrode and larger current density for the conversion of CO2 to formate than pristine ZnO and ZnSnO3. In particular, the FEs of the C1 products (CO + HCOO−) exceed 98% over the potential window. The experimental measurements combined with theoretical calculations revealed that the ZnO in ZnO/ZnSnO3 heterojunction delivers the valence electron depletion and accordingly optimizes Zn d‐band center, which results in moderate Zn–O hybridization of HCOO* and weakened Zn–C hybridization of competing COOH*, thus greatly boosting the HCOOH generation. Our study highlights the importance of charge redistribution in catalysts on the selectivity of electrochemical CO2 reduction.

Abstract The development of fluorescent probe with high spectral overlap with analyte is favorable for the sensing applications via inner filter effect, which requires facile tuning of their structure and photophysical properties. Herein, the rational design of blue emissive carbon dots (B‐CDs) is reported for effective detection of metronidazole (MNZ) in both deionized water and real water samples. The design strategy is based on the elaborate choice of precursors that allows precise control over the nitrogen‐doping degree and graphitization content of B‐CDs. As a result, the as‐prepared B‐CDs exhibit a specific and quick fluorescence quenching response to MNZ via the IFE mechanism because of their good spectral overlap in absorbance. This approach shows a broad linear range (0.5–160 µm), low detection limit (0.1 µm), and moderate selectivity, suggesting its promise for practical applications in environmental sensing.

Pesticides are widely used in agriculture, but their impact on the environment and human health is a major concern. While much attention has been given to their presence in soil, water, and food, there have been few studies on airborne pesticide pollution on a global scale. This study aimed to assess the extent of atmospheric pesticide pollution in countries worldwide and identify regional differences using a scoring approach. In addition to analyzing the health risks associated with pesticide pollution, we also examined agricultural practices and current air quality standards for pesticides in these countries. The pollution scores varied significantly among the countries, particularly in Europe. Asian and Oceanic countries generally had higher scores compared to those in the Americas, suggesting a relatively higher level of air pollution caused by pesticides in these regions. It is worth noting that the current pollution levels, as assessed theoretically, pose minimal health risks to humans. However, studies in the literature have shown that excessive exposure to pesticides present in the atmosphere has been associated with various health problems, such as cancer, neuropsychiatric disorders, and other chronic diseases. Interestingly, European countries had the highest overall pesticide application intensities, but this did not necessarily correspond to higher atmospheric pesticide pollution scores. Only a few countries have established air quality standards specifically for pesticides. Furthermore, pollution scores across states in the USA were investigated and the global sampling sites were mapped. The findings revealed that the scores varied widely in the USA and the current sampling sites were limited or unevenly distributed in some countries, particularly the Nordic countries. These findings can help global relevant environmental agencies to set up comprehensive monitoring networks. Overall, the present research highlights the need to create a pesticide monitoring system and increase efforts to enhance pesticide regulation, ensure consistency in standards, and promote international cooperation.

Optical frequency combs (OFCs) with programmable free spectral range and high optical carrier-to-noise ratio (CNR) play a crucial role in diverse research fields, including telecommunications, spectroscopy, quantum information, astronomy, sensing, and imaging. Unfortunately, the presence of stochastic noise often results in degraded optical CNR, leading to limited communication performance and measurement accuracy in comb-based systems. There is a lack of effective and flexible methods to improve the CNR of OFCs contaminated by broadband noise, hampering their widespread utilization. To address this challenge, we propose a four-wave mixing based spectral Talbot amplifier to purify OFCs flexibly. Our approach employs programmable spectral phase filters followed by a nonlinear Kerr medium to regenerate an OFC with superior CNR. In our experimental demonstration, we regenerated a 165-GHz spaced CNR enhanced OFC from a noise-dominated comb source spaced at 11 GHz, achieving up to ∼11-dB CNR improvement. The technique allows for a user-defined purification factor m to range from 7 to 15. Furthermore, our scheme demonstrates flexibility in adjusting the wavelengths of the regenerated comb lines via a tunable optical delay line without the need for a tunable seed laser. We also investigated the impact of the pump and signal on the regenerated comb experimentally and studied the influence of dispersion mismatch on the suppression of undesired sidebands numerically. Our proposed scheme presents a powerful alternative for programmable purification, manipulation, and detection of noise-dominated spectral waveforms.

An increasing number of gene mutations associated with epilepsy have been identified, some linked to gray matter heterotopia—a common cause of drug-resistant epilepsy. Current research suggests that gene mutation-associated epilepsy should not be considered a contraindication for surgery in epilepsy patients. At present, stereoelectroencephalography-guided radiofrequency thermocoagulation is an important method to treat periventricular nodular heterotopia-associated drug-resistant epilepsy. We present a case of drug-resistant epilepsy, accompanied by periventricular nodular heterotopia and a heterozygous mutation of the RELN gene, successfully treated with radiofrequency thermocoagulation, resulting in a favorable outcome.

As a mode of animal management, grazing on pasture has the potential to improve animal performance and provide healthy meat. However, there is little information about the effects of lamb meat quality grazed on sainfoin pasture. Therefore, the present study was conducted to compare the fatty acid composition and oxidative stability of growing lambs. The twenty-four lambs were randomly divided into grazing on sainfoin pasture (GS) or feeding indoors pelleted total mixed ration (FI). The results show that GS had the higher polyunsaturated fatty acids (PUFA), especially n-3 PUFA (P = 0.002), and beneficial for nutritional index of fatty acid. Corresponding that GS had lower the Thiobarbituric acid reactive substance (TBARS) in raw (P = 0.005) and cooked meat (P = 0.008). The GS had higher total phenols (P = 0.021), ferric reducing antioxidant power (FRAP) (P = 0.048) and α-Tocopherol of meat (P = 0.004). In conclusion, grazing on sainfoin pasture in lambs can improve muscle fatty acid composition and oxidative stability than feeding indoors.

Objectives The reconstruction of bone defects in tibial revision knee arthroplasty is challenging. In this study, we evaluated the primary stability of a novel three‐dimensional (3D)‐printed custom‐made metaphyseal cone for Anderson Orthopedic Research Institute (AORI) IIb or III bone defect reconstruction in tibial revision knee arthroplasty using the combination of finite‐element analysis and biomechanical experiments. Methods In the finite‐element analysis, AORI II b and III medial tibial bone defects were designed at varying depths. A novel 3D‐printed custom‐made metaphyseal cone was designed and used to reconstruct the bone defect with or without a stem in simulated revision total knee arthroplasty (RTKA). A no‐stem group and a stem group were established (based on whether a stem was used or not). Von Mises stress and micromotion were calculated with varying depths of bone defects, ranging from 5 mm to 35 mm, and then micromotions at the bone–implant interface were calculated and compared with the critical value of 150 μm. In the biomechanical experiment, the no‐stem group was used, and the same bone defects were made in four synthetic tibias using patient‐specific instruments. Micromotions at the bone–implant interface were investigated using a non‐contact optical digital image correlation system and compared with the critical value of 150 μm. Results When the bone defect was

Abstract Under double-seam mining, the main roadway surrounding rock is affected by the superposition of the advanced stress of the two-seam coal working faces. The stress superposition mode and degree are of great significance to the width calculation of the protective coal pillar and the determination of the critical control direction of the surrounding rock. This paper uses theoretical analysis, numerical simulation, and site engineering practice to carry out targeted research. The conclusions are as follows: Under different lateral pressure coefficients, the superposition evolution law of maximum principal stress direction of two coal seams with different offsets; Two developmental trends and three types of evolution models of J 2 peak zone (the critical area of the stress increase and deflection changes) under different superimposed loading modes are summarized. Based on the typical asymmetric evolution model of the J 2 peak zone, an asymmetric truss-cable co-anchoring method is proposed aimed at the J 2 critical zone. The field monitoring results show that the main roadway surrounding rock is stable after support when the upper coal seam protective coal pillar is left 80 m, and the lower one is 60 m wide. It is of great reference importance for similar engineering practices.

Background: As an important part of the tongue, the tongue coating is closely associated with different disorders and has major diagnostic benefits. This study aims to construct a neural network model that can perform complex tongue coating segmentation. This addresses the issue of tongue coating segmentation in intelligent tongue diagnosis automation. Method: This work proposes an improved TransUNet to segment the tongue coating. We introduced a transformer as a self-attention mechanism to capture the semantic information in the high-level features of the encoder. At the same time, the subtraction feature pyramid (SFP) and visual regional enhancer (VRE) were constructed to minimize the redundant information transmitted by skip connections and improve the spatial detail information in the low-level features of the encoder. Results: Comparative and ablation experimental findings indicate that our model has an accuracy of 96.36%, a precision of 96.26%, a dice of 96.76%, a recall of 97.43%, and an IoU of 93.81%. Unlike the reference model, our model achieves the best segmentation effect. Conclusion: The improved TransUNet proposed here can achieve precise segmentation of complex tongue images. This provides an effective technique for the automatic extraction in images of the tongue coating, contributing to the automation and accuracy of tongue diagnosis.

This study aimed to evaluate the impact of dietary energy and protein levels on the meat quality and metabolomic profile of Yunshang black goats. For this, 80 Yunshang black goats (male, 6 months old, with a mean live body weight of 35.82 ± 2.79 kg) were used in a completely randomized design with a 2 × 2 factorial dietary arrangement. The dietary treatments were (1) high energy (9.74 MJ/kg) with high protein (12.99%) (HEHP), (2) high energy (9.76 MJ/kg) with low protein (10.01%) (HELP), (3) low energy (8.18 MJ/kg) with high protein (13.04%) (LEHP), and (4) low energy (8.14 MJ/kg) with low protein (10.05%) (LELP). The experiment lasted 64 days, including 14 days for dietary adaptation and a 50-day feeding trial. At the end of the experiment, four animals from each treatment were slaughtered to assess their meat quality and metabolomic profiles. The pH value was greater for the goats fed the LELP diet compared with the other treatments. The LEHP-fed group’s meat was brighter (L*) than that of the other three groups. The HEHP-fed group had considerably more tender meat (p < 0.05) compared with the LEHP-fed group. Moreover, 72 and 183 differentiated metabolites were detected in the longissimus muscle samples by using gas chromatography–mass spectrometry and liquid chromatography–tandem mass spectrometry, respectively. The hydropathy and volatilities of raw meat were different (p < 0.05), suggesting changes in the meat flavor because of the dietary treatments. Based on the results, it can be concluded that feeding a high-energy- and high-protein-containing diet improved the tenderness, flavor, and fatty acid contents of mutton.

Aircraft ducts play an indispensable role in various systems of an aircraft. The regular inspection and maintenance of aircraft ducts are of great significance for preventing potential failures and ensuring the normal operation of the aircraft. Traditional manual inspection methods are costly and inefficient, especially under low-light conditions. To address these issues, we propose a new defect detection model called LESM-YOLO. In this study, we integrate a lighting enhancement module to improve the accuracy and recognition of the model under low-light conditions. Additionally, to reduce the model’s parameter count, we employ space-to-depth convolution, making the model more lightweight and suitable for deployment on edge detection devices. Furthermore, we introduce Mixed Local Channel Attention (MLCA), which balances complexity and accuracy by combining local channel and spatial attention mechanisms, enhancing the overall performance of the model and improving the accuracy and robustness of defect detection. Finally, we compare the proposed model with other existing models to validate the effectiveness of LESM-YOLO. The test results show that our proposed model achieves an mAP of 96.3%, a 5.4% improvement over the original model, while maintaining a detection speed of 138.7, meeting real-time monitoring requirements. The model proposed in this paper provides valuable technical support for the detection of dark defects in aircraft ducts.

The use of carbon nanomaterials in ultra-high-performance concrete (UHPC) to improve its mechanical properties and durability is growing. Graphene oxide (GO) has emerged as one of the most promising nanomaterials in recent years for enhancing the properties of UHPC. The majority of research so far has been on the properties of UHPC enhanced with GO, but its high cost has limited its application in engineering. This work suggests a machine learning (ML)-based approach to optimize the mix ratio in order to lower the cost of graphene oxide-modified UHPC. To do this, an artificial neural network (ANN) is used to create the prediction model for the 28-day compressive strength and slump flow of UHPC. The performance of this model is then compared using nine different ML techniques. Subsequently, considering the restrictions of the UHPC component content, component proportion, and absolute volume, a genetic algorithm (GA) is adopted to lower the UHPC cost. The sensitivity analysis is carried out in the end. This study’s findings indicate that there is a decent degree of prediction accuracy since the difference between the ANN model’s predictions and the experimental outcomes is just 10%. The cost of UHPC optimized by GA is reduced to 776 $/m3, significantly lower than the average cost of UHPC.

Molybdenum disulfide (MoS2), a typical layered material, has important applications in various fields, such as optoelectronics, catalysis, electronic devices, sensors, and supercapacitors. Extensive research has been carried out on few-layered MoS2 in the field of electrochemistry due to its large specific surface area, abundant active sites and short electron transport path. However, the preparation of few-layered MoS2 is a significant challenge. This work presents a simple one-pot hydrothermal method for synthesizing few-layered MoS2. Furthermore, it investigates the exfoliation effect of different amounts of sodium borohydride (NaBH4) as a stripping agent on the layer number of MoS2. Na+ ions, as alkali metal ions, can intercalate between layers to achieve the purpose of exfoliating MoS2. Additionally, NaBH4 exhibits reducibility, which can effectively promote the formation of the metallic phase of MoS2. Few-layered MoS2, as an electrode for supercapacitor, possesses a wide potential window of 0.9 V, and a high specific capacitance of 150 F g−1 at 1 A g−1. This work provides a facile method to prepare few-layered two-dimensional materials for high electrochemical performance.

Abstract The most common kind of acute leukemia in adults is acute myeloid leukemia (AML), which is often treated with induction chemotherapy regimens followed by consolidation or allogeneic hematopoietic stem cell transplantation (HSCT). However, some patients continue to develop relapsed or refractory AML (R/R-AML). Small molecular targeted drugs require long-time administration. Not all the patients hold molecular targets. Novel medicines are therefore needed to enhance treatment outcomes. T cells and natural killer (NK) cells engineered with chimeric antigen receptors (CARs) that target antigens associated with AML have recently been produced and are currently being tested in both pre-clinical and clinical settings. This review provides an overview of CAR-T/NK treatments for AML.

ABSTRACTLimited information on the virome and bacterial community hampers our ability to discern systemic ecological risk factors that cause cattle diarrhea, which has become a pressing issue in the control of disease. A total of 110 viruses, 1,011 bacterial genera, and 322 complete viral genomes were identified from 70 sequencing samples mixed with 1,120 fecal samples from 58 farms in northeast China. For the diarrheic samples, the identified virome and bacterial community varied in terms of composition, abundance, diversity, and geographic distribution in relation to different disease-associated ecological factors; the abundance of identified viruses and bacteria was significantly correlated with the host factors of clinical status, cattle type, and age, and with environmental factors such as aquaculture model and geographical location (P < 0.05); a significant interaction occurred between viruses and viruses, bacteria and bacteria, as well as between bacteria and viruses (P < 0.05). The abundance of SMB53, Butyrivibrio, Facklamia, Trichococcus, and Turicibacter was significantly correlated with the health status of cattle (P < 0.05). The proportion of BRV, BCoV, BKV, BToV, BoNoV, BoNeV, BoAstV, BEV, BoPV, and BVDV in 1,120 fecal samples varied from 1.61% to 12.05%. A series of significant correlations were observed between the prevalence of individual viruses and the disease-associated ecological factors. A genome-based phylogenetic analysis revealed high variability of 10 bovine enteric viruses. The bovine hungarovirus was initially identified in both dairy and beef cattle in China. This study elucidates the fecal virome and bacterial community signatures of cattle affected by diarrhea, and reveals novel disease-associated ecological risk factors, including cattle type, cattle age, aquaculture model, and geographical location.IMPORTANCEThe lack of data on the virome and bacterial community restricts our capability to recognize ecological risk factors for bovine diarrhea disease, thereby hindering our overall comprehension of the disease’s cause. In this study, we found that, for the diarrheal samples, the identified virome and bacterial community varied in terms of composition, abundance, diversity, configuration, and geographic distribution in relation to different disease-associated ecological factors. A series of significant correlations were observed between the prevalence of individual viruses and the disease-associated ecological factors. Our study aims to uncover novel ecological risk factors of bovine diarrheal disease by examining the pathogenic microorganism-host-environment disease ecology, thereby providing a new perspective on the control of bovine diarrheal diseases.

The potential energy curves (PECs) and transition dipole moments (TDMs) of PH+ and PO are computed with the multireference configuration interaction method, and the cross-sections for the radiative association (RA) of PH+ and PO, which is the most efficient way to form the ground states, are presented via the quantum mechanical (QM) theory and computed using ab initio molecular data. The thermal rate coefficients are also expressed and fitted with the standard formula kT=AT300αe−βT in the range of 10 K–15,000 K. Meanwhile, the photodissociation, that is the inverse process of RA for PH+, is also studied, including eight photodissociation channels for the computation of state-resolved cross-sections. Careful comparisons with the Leiden Observatory database are made. Considering the cross-sections mentioned above, the local thermodynamic equilibrium cross-sections at the temperatures of 0, 500, 1,000, and 2,000 K are also shown. We expect the results to be helpful for studies of phosphorus chemistry in the interstellar medium and planetary atmospheres.

Physical activity levels have the potential to impact human internal exposure to environmental chemicals. However, the current lack of simple modeling approaches hinders the high-throughput screening of chemical exposure at different physical activity levels. To address this gap, this study proposes a straightforward model for assessing human internal exposure to chemicals. Our approach is based on the physiologically based kinetic (PBK) model and utilizes the metabolic equivalent of task (MET) to characterize internal exposure to chemicals at varying activity levels. To facilitate the application of this model, we have developed an Excel-based operation tool, allowing users to easily modify the MET value and generate simulation results for different physical activity levels. The simulation results demonstrate that as physical activity levels increase, the biotransfer factors (BTFs) of chemicals decrease, suggesting that higher physical activity levels reduce the bioaccumulation potential of chemicals. The intensified physical activity enhances the overall elimination kinetics of chemicals from the human body. However, the simulated concentrations of chemicals in the human body increase with higher physical activity levels, due to the significantly increased external exposure to chemicals, such as through inhalation. Our proposed modeling approach, along with the operational tool, enables high-throughput simulation of human chronic internal exposure to chemicals at different physical activity levels, where the findings can assist in screening chemicals for further health risk assessment. To accomplish this, the model incorporates certain assumptions and utilizes generic model input values. However, due to the intricate nature of the interaction between external and internal exposures at different physical activity levels, validating the simulation through experimental studies becomes challenging and is not performed in this study. For future studies, we recommend incorporating more MET-related physiological input variables, improving energy balance estimates, comprehending external exposure estimates, and conducting cohort studies to enhance and validate the proposed modeling approach.

Abstract Epitaxial growth is one of the most commonly used strategies to precisely tailor heterostructures with well-defined compositions, morphologies, crystal phases, and interfaces for various applications. However, as epitaxial growth requires a small interfacial lattice mismatch between the components, it remains a challenge for the epitaxial synthesis of heterostructures constructed by materials with large lattice mismatch and/or different chemical bonding, especially the noble metal-semiconductor heterostructures. Here, we develop a noble metal-seeded epitaxial growth strategy to prepare highly symmetrical noble metal-semiconductor branched heterostructures with desired spatial configurations, i.e., twenty CdS (or CdSe) nanorods epitaxially grown on twenty exposed (111) facets of Ag icosahedral nanocrystal, albeit a large lattice mismatch (more than 40%). Importantly, a high quantum yield (QY) of plasmon-induced hot-electron transferred from Ag to CdS was observed in epitaxial Ag-CdS icosapods (18.1%). This work demonstrates that epitaxial growth can be achieved in heterostructures composed of materials with large lattice mismatches. The constructed epitaxial noble metal-semiconductor interfaces could be an ideal platform for investigating the role of interfaces in various physicochemical processes.

The last decade has witnessed the rapid development of immersive virtual reality (IVR) and its application in various contexts. However, its application in supporting real-time virtual collaboration has been quite rare due to technical barriers and the lack of validated design principles. To address this research gap, this study designed and developed an IVR space to enable multiuser synchronous co-located collaboration to complete a fantasy game. An evaluation study (N = 95) was conducted to explore its useful design considerations and the influencing factors for collaboration experience in the game. The IVR space was enabled by the simultaneous localization and mapping (SLAM)-based inside-out tracking technique and was informed by four essential design considerations for promoting effective collaboration in IVR, namely, the role script, learning task, collaboration mechanism, and communication design. The study results revealed that students in general were satisfied with their collaboration experience in IVR, with social presence and collaboration competency as significant predictors of collective efficacy and social experience. Based on both quantitative and qualitative results, this study proposes four validated principles for designing effective IVR spaces to support synchronous co-located collaboration.

Guttation consumption is a potential pathway of pesticide residue exposure in honeybees. However, modeling tools for assessing honeybee exposure to pesticide residues in guttation drops are lacking. In this study, we propose an indicator-based approach for qualitatively or quantitatively analyzing the guttation-based exposure pathway, allowing us to conduct region-specific pesticide residue exposure assessments for honeybees. Exposure scores (the product of guttation production and residue level scores) were established to compare or rank honeybee exposure to pesticide residues via guttation intake across locations using three specified indicators (i.e., air temperature, relative humidity, and precipitation intensity). Warm, dry regions had high residue level scores (indicating high residue levels in guttation), whereas cold, wet regions had high guttation production scores (indicating high possibilities of guttation formation on leaf surfaces); their exposure scores were a combination of these two values. We evaluated and ranked honeybee exposure to imidacloprid residue across regions in Brazil, China, the United States, and selected European Union member states, revealing that pesticide application in many Brazilian federative units may raise honeybee risks due to high exposure scores. We also compared the guttation pathway to other common exposure pathways (nectar and pollen), suggesting that for some moderately lipophilic compounds, the guttation exposure pathway may not be ignored and should be further evaluated.

Peas are among the most popular leguminous plants, consumed by both humans and animals in large quantities. Pesticides are widely used globally to increase pea yield, and as a result, pesticide residues can be taken up by pea plants and bioaccumulate in their fruits, including peas and pods. However, there is a lack of modeling approaches available to predict residue concentrations in peas. To address this issue, a pod fruit model (specifically designed for neutral organic compounds) was proposed to simulate the bioaccumulation process of pesticide residues in pea plants, which was developed by modifying a peel-like uptake model. The simulation results, based on green pea as the modeling demonstration, reveal that moderately-lipophilic pesticides (i.e., log KOW around 3) have higher simulated concentrations in peas at harvest compared to hydrophilic (i.e., log KOW less than 0) or highly-lipophilic (i.e., log KOW over 5) pesticides, which is due to the enhanced uptake process of moderately-lipophilic compounds in the pod-pea system, such as their ability to penetrate the pod cuticle and be transported via phloem sap. The sensitivity test and variability analysis conducted in this study revealed that the degradation kinetics, including metabolism, hydrolysis, and photolysis, had a significant impact on moderately-lipophilic pesticides due to their high simulated concentrations in the pea plant. This can result in substantial loss of residue mass via degradation. The validation of the model demonstrated that the simulation results, specifically residue concentrations in the fruit, were consistent with the harvested data. However, some inconsistency was observed immediately after pesticide application, which could be attributed to plant growth dynamics and initial surface mass distributions. The proposed pod fruit model provides new insights into the bioaccumulation process of pesticide residues in pea plants and enables high-throughput simulations of residue concentrations at harvest. To enhance the performance of the pod fruit model, future research should consider plant growth dynamics, plant uptake of ionizable compounds, and initial mass distribution functions.

Soil quality standards for pesticides play a crucial role in protecting plants and preventing potential health hazards to humans. Here we discuss modeling approaches to define pesticide soil quality standards from two effect endpoints, which ensures consistency throughout the entire pesticide life cycle from application to human exposure assessment. Given that pesticides are applied in a pulse-like emission pattern and their soil concentrations change over time, both a ceiling legal limit and an average legal limit for pesticide soil quality standards should apply to the initial pesticide application practice and the potential human health effect. The timing intervals for pesticide application and the dissipation half-life in the soil can be used to quantify the relationship between the ceiling and average legal limits. By analyzing primary exposure pathways related to soil contamination, the average legal limit can be linked to theoretical human health risks, which requires a comprehensive evaluation for an adequate safety margin, including human interactions with soil, exposure assessment of soil pesticides, and allocation exposure assessment. To establish acceptable human health risks, the average legal limit can be determined, and the ceiling legal limit can be estimated based on the quantitative relationship between the ceiling and average legal limits. Additionally, we discuss situation-specific factors, including climate-pattern and behavior-pattern factors, to define pesticide soil quality standards to further complete the modeling framework. We hope insights presented in this paper will assist regulatory agencies worldwide in defining pesticide soil quality standards that meet their specific regulatory needs throughout the entire pesticide life cycle.

Pesticide application techniques are critical not only for integrated pest management (IPM) but also for food and environmental safety. Assessing pesticide application efficiency on plants can help optimize IPM and reduce pesticide environmental impacts. With hundreds of pesticides registered for use in agriculture, this study proposed a modeling approach based on plant uptake models for generalizing routes of plant chemical exposures that can correspond to different types of pesticide application methods and evaluating their respective efficiency on plants. Three representative pesticide application methods (i.e., drip irrigation, foliar spray, and broadcast application) were selected for modeling simulations. The simulation results for three representative pesticides (i.e., halofenozide, pymetrozine, and paraquat) revealed that the soil-based transpiration exposure route facilitated the bioaccumulation of moderately lipophilic compounds in leaves and fruits. While the plant surface-based exposure route (i.e., leaf cuticle penetration) made it easier for highly lipophilic compounds to enter plants, moderately lipophilic pesticides (i.e., log KOW ∼ 2) were more soluble in phloem sap, which enhanced their subsequent transport within plant tissues. In general, moderately lipophilic pesticides had the highest simulated residue concentrations in plant tissues for the three specific application methods, indicating they had the highest application efficiency due to their enhanced uptake routes (via transpiration and surface penetration) and increased solubility in xylem and phloem saps. Compared to foliar spray and broadcast application, drip irrigation produced higher residue concentrations for a wide variety of pesticides, exhibiting the highest application efficiency for many pesticides, especially for moderately lipophilic compounds. Future research should incorporate plant growth stages, crop safety, pesticide formulations, and multiple application events into the modeling approach for understanding pesticide application efficiency evaluation.

The role of eiptranscriptomic modifications in autophagy is unclear. Here, the authors show that the m6A reader YTHDF3 functions as a nutrient responder to recognize upregulated m6A modification, promoting FOXO3 translation to subsequently initiate autophagy.

Acute myeloid leukemia (AML) is a hematologic carcinoma that has seen a considerable improvement in patient prognosis because of genetic diagnostics and molecularly-targeted therapies. Nevertheless, recurrence and drug resistance remain significant obstacles to leukemia treatment. It is critical to investigate the underlying molecular mechanisms and find solutions. Non-coding RNAs (ncRNAs), such as microRNAs (miRNAs), circular RNAs, long non-coding RNAs, and pseudogenes, have been found to be crucial components in driving cancer. The competing endogenous RNA (ceRNA) mechanism has expanded the complexity of miRNA-mediated gene regulation. A great deal of literature has shown that ncRNAs are essential to the biological functions of the ceRNA network (ceRNET). NcRNAs can compete for the same miRNA response elements to influence miRNA-target RNA interactions. Recent evidence suggests that ceRNA might be a potential biomarker and therapeutic strategy. So far, however, there have been no comprehensive studies on ceRNET about AML. What is not yet clear is the clinical application of ceRNA in AML. This study attempts to summarize the development of research on the related ceRNAs in AML and the roles of ncRNAs in ceRNET. We also briefly describe the mechanisms of ceRNA and ceRNET. What's more significant is that we explore the clinical value of ceRNAs to provide accurate diagnostic and prognostic biomarkers as well as therapeutic targets. Finally, limitations and prospects are considered.

Efficient transport in vertical pipeline hydraulic lifting systems is vital for coarse-grained ore, necessitating a deep comprehension of the settling traits of coarse mineral particles. In this study, we conducted a series of settling experiments on individual coarse particles in Newtonian fluids with varying viscosities, employing a self-designed and manufactured settling apparatus. A total of 133 sets of experimental data on the free settling of coarse particles in Newtonian fluids were obtained by recording the particle settling process with a high-speed camera and applying image processing techniques. A mechanical model was employed to perform statistical analysis on the experimental data and establish a predictive model for the drag coefficient and an explicit predictive model for the settling terminal velocity of coarse-grained ore in Newtonian fluids. The average relative errors between the predicted values and experimental values of the drag coefficient and settling terminal velocity models are 4.26% and 7.34%, respectively. This confirms the reliability of the provided predicted model, providing a theoretical foundation for determining the hydraulic lifting speed of coarse mineral particles in vertical pipelines for deep mining.

Single-layer tunnel lining using shotcrete has the significant advantages of reducing the tunnel excavation volume and saving construction materials, which has been gradually applied in tunnel construction. The high-performance concretes are generally adopted in single-layer tunnel lining for enhancing the bearing capacity of the tunnel lining, whereas the single-layer tunnel lining may still induce damages due to the adverse conditions such as shallow buried depth of the tunnel, and further study related to its application condition is thus required. This paper presents a study of the single-layer tunnel lining with shotcrete employed for supporting the large-span tunnel, in which the reinforcement ribs are also adopted in the single-layer lining for improving the lining stiffness and strength. The study is implemented using numerical simulation, focusing on the safety and performance variation of the single-layer tunnel lining influenced from the varied lining thicknesses and shallow buried depths of the tunnel. The results shows that the single-layer tunnel lining has the obvious advantage of toughness in significantly absorbing large deformation of surrounding rocks and improving the ability to resist lining cracking. The results also demonstrate that the single-layer tunnel lining with shotcrete and reinforcement ribs can safely support the large-span tunnel, in which the stability and safety of the large-span tunnel are confirmed from both the tunnel deformation and lining stresses. Moreover, the factors related to both the lining thickness and shallow buried depth of the tunnel have great influence on the single-layer tunnel lining with shotcrete and reinforcement ribs, in which the insufficient lining thickness and excessive shallow buried depth of the tunnel can induce the damages of the single-layer tunnel lining due to shotcrete stresses exceeding its strength. This study provides some references of employing the single-layer tunnel lining with shotcrete and reinforcement ribs for supporting large-span tunnel.

The two-step layer-by-layer (LBL) deposition of donor and acceptor films enables desired vertical phase separation and high performance in organic solar cells (OSCs), which becomes a promising technology for large-scale printing devices. However, limitations including the use of toxic solvents and unpredictable infiltration between donor and acceptor still hinder the commercial production of LBL OSCs. Herein, we developed a water-based nanoparticle (NP) ink containing donor polymer to construct a mesoscale structure that could be infiltrated with an acceptor solution. Using non-halogen o-xylene for acceptor deposition, the LBL strategy with a mesoscale structure delivered outstanding efficiencies of 18.5% for binary PM6:L8-BObased LBL OSCs. Enhanced charge carrier mobility and restricted trap states were observed in the meso-LBL devices with optimized vertical morphology. It is believed that the findings in this work will bring about more research interest and effort on eco-friendly processing in preparation for the industrial production of OSCs.

BackgroundThough omega-3 fatty acids reduce seizures in several animal models, considerable controversy exists regarding the association between omega-3 fatty acids and epilepsy in human.ObjectiveTo assess whether genetically determined human blood omega-3 fatty acids are causally associated with the risk of epilepsy outcomes.MethodsWe conducted a two-sample Mendelian randomization (MR) analysis by applying summary statistics of genome-wide association study datasets of both exposure and outcomes. Single nucleotide polymorphisms significantly associated with blood omega-3 fatty acids levels were selected as instrumental variables to estimate the causal effects on epilepsy. Five MR analysis methods were conducted to analyze the final results. The inverse-variance weighted (IVW) method was used as the primary outcome. The other MR analysis methods (MR-Egger, weighted median, simple mode, and weighted mode) were conducted as the complement to IVW. Sensitivity analyses were also conducted to evaluate heterogeneity and pleiotropy.ResultsGenetically predicted the increase of human blood omega-3 fatty acids levels was associated with a higher risk of epilepsy (OR = 1.160, 95%CI = 1.051–1.279, P = 0.003).ConclusionsThis study revealed a causal relationship between blood omega-3 fatty acids and the risk of epilepsy, thus providing novel insights into the development mechanism of epilepsy.