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This study delves into the opportunities and challenges associated with the deployment of AI tools in the education sector. It systematically explores the potential benefits and risks inherent in utilizing these tools while specifically addressing the complexities of identifying and preventing academic dishonesty. Recognizing the ethical dimensions, the paper further outlines strategies that educational institutions can adopt to ensure the ethical and responsible use of AI tools. Emphasizing a proactive stance, the paper suggests that by implementing these strategies, schools can harness the benefits of AI tools while mitigating the risks associated with potential misuse. As the adoption of AI tools in education continues to expand, all stakeholders must stay abreast of the latest developments in the field. This knowledge equips educators to navigate the opportunities and challenges posed by AI tools, fostering a learning environment that is both secure and conducive to empowering students to realize their full potential.

Groundwater is an important water supply source in Xining City. Previous works have found that iron-rich groundwater limits water development and utilization. However, few studies focus on the distribution characteristics and mechanism of iron-rich groundwater in different types of aquifers in Xining City. Based on the hydrochemical data of 144 groundwater samples, combined with the geological and hydrogeological conditions, the distribution characteristics and influencing factors of iron content in groundwater in different aquifers were analyzed by methods of statistics and geostatistics. The results show that the exceeding standard ratio of iron in groundwater of unconsolidated sediments aquifer (Area Ⅰ) is 27. 85%, which is 1. 6 times and 2. 7 times higher than that of clastic rocks fissure-pore aquifer (Area Ⅱ) and bedrock aquifer (Area Ⅲ), respectively. The proportion of iron-rich groundwater (concentration greater than 0. 3 mg/L) in construction land area is significantly higher than in areas with other land use types. The redox environment and human activities (such as industrial wastewater, domestic sewage, and infiltration of iron-rich river water) may be the main factors affecting the increase of iron content in groundwater in Area I. In addition to the redox environment, Agricultural nitrogen fertilizer use and domestic sewage discharge are also important factors affecting iron-rich groundwater in Area Ⅱ. The iron-rich groundwater in Area Ⅲ is mainly controlled by redox conditions. On the regional scale, the distribution of iron-rich groundwater presents in bands or spots along the river. The iron deposits releasing in the primary strata and human activities (industrial wastewater) are the main source of iron ions in the shallow groundwater in the study area. The migration and enrichment of iron in groundwater are mainly controlled by redox conditions, and affected by the runoff condition, without relation to pH and salt effect. This study can provide scientific basis for urban water environment management in Xining City and similar arid and semi-arid areas.

Abstract With the support of our government’s commitment to the energy sector, the installed capacity of wind power will continue to grow. However, due to the instability of wind power, accurate prediction of wind power output is essential for effective grid dispatch. In addition, data privacy and protection have become paramount in today’s society. Traditional wind forecasting methods rely on centralized data, which raises concerns about data privacy and data silos. To address these challenges, we propose a hybrid approach that combines federated learning and deep learning for wind power forecasting. In our proposed method, we use a bidirectional long short-term memory (BILSTM) neural network as the basic prediction model to improve the prediction accuracy. Then, the model is integrated into the federated learning framework to form the Fed-BILSTM prediction method. In addition, we have introduced cloud computing technology into the Fed-BILSTM method, using cloud resources for model training and parameter update. Participants share model parameters instead of sharing raw data, which solves data privacy concerns. We compared Fed-BILSTM with traditional forecasting methods. Experimental results show that the proposed Fed-BILSTM is better than the traditional prediction method in terms of prediction accuracy. What’s more, Fed-BILSTM can effectively protect data privacy compared to traditional centralized forecasting methods while ensuring prediction performance.

Abstract Background In Chinese culture, the concept of Mianzi holds significant importance in interpersonal interactions. Mianzi represents one’s social standing, dignity, and reputation, influencing behaviors and decisions within various contexts. Mianzi consciousness manifests in two primary forms: proactive and defensive. Proactive Mianzi consciousness involves efforts to enhance one’s social image, while defensive Mianzi consciousness focuses on protecting one’s existing reputation. Analyzing the impact of the two Mianzi consciousness dimensions on individuals’ attitudes and behaviors is effective for understanding interpersonal dynamics in China. This study specifically examined the relationship between high Mianzi consciousness congruence and unethical pro-organizational behavior (UPB). UPB refers to actions taken by employees that are intended to benefit their organization but are unethical or morally questionable. By investigating how congruence in proactive and defensive Mianzi consciousness influences the likelihood of engaging in UPB, this research aimed to uncover the underlying social and psychological mechanisms driving such behavior. Methods Employing polynomial regression and response surface analysis method, this study developed a model that combines the proactive Mianzi consciousness and the defensive Mianzi consciousness into different Mianzi management strategies and tested the relationship between high Mianzi consciousness congruence and UPB. Results Sample data collected at two time points one month apart supported all hypotheses. Specifically, the findings revealed that high levels of Mianzi consciousness congruence (i.e., all-around type in Mianzi management strategies) positively relate to UPB, and verified the mediation effect of external work locus of control and the moderation effect of relational psychological contract. Conclusion This research advanced a novel, synergistic perspective on the role of social Mianzi and contributed to the localized UPB research, thus helping to find a path to prevent UPB from occurring in the Chinese sociocultural context.

[Introduction] In response to the inability of existing communication conditions to meet the intelligent O&M and ecological monitoring needs of offshore wind farm, this article explores and proposes a 5G customized network scheme to solve the problems of poor signal accessibility, incomplete network coverage, and low smoothness in offshore wind farms. [Methods] In this paper, a comprehensive O&M and monitoring scheme was proposed by using 5G customized network technology, which was as follows: through the deployment of 5G macro base stations outdoors, 5G indoor distribution in towers, and underwater laying of optical networks, the 3D coverage of wind farm communication networks was realized; Based on 5G slicing technology, one network could be used for multiple purposes to meet the needs of offshore wind farms for network differentiation; computing nodes were deployed in the centralized control center computer room, and private network data was forwarded through the edge UPF (user plane function) to achieve computing-network integration. [Result] The intelligent management and ecological environment monitoring scheme for offshore wind farms based on 5G technology proposed in this article has been piloted and tested based on the project. The test results show that the maximum effective coverage radius of 5G base stations reaches 11.3 km, and the stable transmission uplink rate reaches 5 Mbps, meeting the needs of observation data return and unmanned ship video return in the sea area. By deploying two 2.1G 8TR enhanced base stations on the booster station and wind turbine to enhance sea area coverage, the pull-net test around the wind farm verified that the 5G private network can effectively cover wind farms, with a coverage rate of 98.4%, which can basically meet the coverage needs of the entire wind farm. [Conclusion] This scheme utilizes a 5G private network to cover the sea area of the wind farm and achieves underwater communication through STN (Smart Transport Network) and underwater optical networks. Consequently, it innovatively constructs a 3D ocean monitoring and communication network, laying the communication foundation for the intelligent management and ecological environment monitoring of offshore wind farms.

Abstract Background Conventional single-energy CT can only provide a raw estimation of electron density (ED) for dose calculation by developing a calibration curve that simply maps the HU values to ED values through their correlations. Spectral CT, also known as dual-energy CT (DECT) or multi-energy CT, can generate a series of quantitative maps, such as ED maps. Using spectral CT for radiotherapy simulations can directly acquire ED information without developing specific calibration curves. The purpose of this study is to assess the feasibility of utilizing electron density (ED) maps generated by a novel dual-layer detector spectral CT simulator for dose calculation in radiotherapy treatment plans. Methods 30 patients from head&neck, chest, and pelvic treatment sites were selected retrospectively, and all of them underwent spectral CT simulation. Treatment plans based on conventional CT images were transplanted to ED maps with the same structure set, including planning target volume (PTV) and organs at risk (OARs), and the dose distributions were then recalculated. The differences in dose and volume histogram (DVH) parameters of the PTV and OARs between the two types of plans were analyzed and compared. Besides, gamma analysis between these plans was performed by using MEPHYSTO Navigator software. Results In terms of PTV, the homogeneity index (HI), gradient index (GI), D2%, D98%, and Dmean showed no significant difference between conventional plans and ED plans. For OARs, statistically significant differences were observed in parotids D50%, brainstem in head&neck plans, spinal cord in chest plans and rectum D50% in pelvic plans, whereas the variance remained minor. For the rest, the DVH parameters exhibited no significant difference between conventional plans and ED plans. All of the mean gamma passing rates (GPRs) of gamma analysis were higher than 90%. Conclusion Compared to conventional treatment plans relying on CT images, plans utilizing ED maps demonstrated similar dosimetric quality. However, the latter approach enables direct utilization in dose calculation without the requirements of establishing and selecting a specific Hounsfield unit (HU) to ED calibration curve, providing an advantage in clinical applications.

Abstract Malus sieversii, commonly known as wild apples, represents a Tertiary relict plant species and serves as the progenitor of globally cultivated apple varieties. Unfortunately, wild apple populations are facing significant degradation in localized areas due to a myriad of factors. To gain a comprehensive understanding of the nutrient status and spatiotemporal variations of M. sieversii, green leaves were collected in May and July, and the fallen leaves were collected in October. The concentrations of leaf nitrogen (N), phosphorus (P), and potassium (K) were measured, and the stoichiometric ratios as well as nutrient resorption efficiencies were calculated. The study also explored the relative contributions of soil, topographic, and biotic factors to the variation in nutrient traits. The results indicate that as the growing period progressed, the concentrations of N and P in the leaves significantly decreased (P P > N. The resorption efficiencies were mainly regulated by nutrient concentrations in fallen leaves. A robust spatial dependence was observed in leaf nutrient concentrations during all periods (70.1–97.9% for structural variation), highlighting that structural variation, rather than random factors, dominated the spatial variation. Nutrient resorption efficiencies (NRE, PRE, and KRE) displayed moderate structural variation (30.2–66.8%). The spatial patterns of nutrient traits varied across growth periods, indicating they are influenced by multifactorial elements (in which, soil property showed the highest influence). In conclusion, wild apples manifested differentiated spatiotemporal variability and influencing factors across various leaf nutrient traits. These results provide crucial insights into the spatiotemporal patterns and influencing factors of leaf nutrient traits of M. sieversii at the permanent plot scale for the first time. This work is of great significance for the ecosystem restoration and sustainable management of degrading wild fruit forests.

Abstract It is of critical importance to address energy poverty in rural areas if inclusive prosperity is to be achieved. Digital finance offers new opportunities to alleviate energy poverty in these regions. However, previous studies have mainly focused on the impact of digital finance on poverty, neglecting research on its impact in rural areas and on specific forms of poverty. This study aims to fill this gap by investigating the impact of digital finance on rural energy poverty. The period 2011–2021 was selected as the observation period, with 31 provinces serving as the study objects. The fixed effects model was employed to investigate the impact of digital finance on rural energy poverty, while exploring the mediating effect. The results indicate that digital finance alleviates the level of rural energy poverty, and this conclusion remains valid following a series of robustness tests. Furthermore, digital finance can indirectly alleviate rural energy poverty through technological innovation and agricultural entrepreneurship activities. Further research indicates that the impact of digital finance on rural energy poverty is more pronounced in regions with abundant human capital, robust government intervention, and minimal urban–rural disparities. This study extends the theoretical support for digital finance to indirectly support rural energy to alleviate poverty. Likewise, this finding provides a new perspective for the government and relevant departments to improve the welfare of residents and alleviate rural energy poverty.

Abstract Background Cis-regulatory elements (CREs) play a pivotal role in gene expression regulation, allowing cells to serve diverse functions and respond to external stimuli. Understanding CREs is essential for personalized medicine and disease research, as an increasing number of genetic variants associated with phenotypes and diseases overlap with CREs. However, existing databases often focus on subsets of regulatory elements and present each identified instance of element individually, confounding the effort to obtain a comprehensive view. To address this gap, we have created CREdb, a comprehensive database with over 10 million human regulatory elements across 1,058 cell types and 315 tissues harmonized from different data sources. We curated and aligned the cell types and tissues to standard ontologies for efficient data query. Results Data from 11 sources were curated and mapped to standard ontological terms. 11,223,434 combined elements are present in the final database, and these were merged into 5,666,240 consensus elements representing the combined ranges of the individual elements informed by their overlap. Each consensus element contains curated metadata including the number of elements supporting it and a hash linking to the source databases. The inferred activity of each consensus element in various cell-type and tissue context is also provided. Examples presented here show the potential utility of CREdb in annotating non-coding genetic variants and informing chromatin accessibility profiling analysis. Conclusions We developed CREdb, a comprehensive database of CREs, to simplify the analysis of CREs by providing a unified framework for researchers. CREdb compiles consensus ranges for each element by integrating the information from all instances identified across various source databases. This unified database facilitates the functional annotation of non-coding genetic variants and complements chromatin accessibility profiling analysis. CREdb will serve as an important resource in expanding our knowledge of the epigenome and its role in human diseases.

AbstractThe main purpose of this study was to explore the changes of biomarkers in different developmental stages of bleomycin-induced pulmonary fibrosis (PF) in rats via comprehensive pathophysiology, UPLC-QTOF/MS metabonomic technology, and 16S rRNA gene sequencing of intestinal microbiota. The rats were randomly divided into normal control and 1-, 2- and 4-week model group. The rat model of PF was established by one-time intratracheal instillation of bleomycin. The levels of inflammatory and fibrosis-related factors such as hydroxyproline (HYP), type III procollagen (COL-III), type IV collagen (COL-IV), hyaluronidase (HA), laminin (LN), interleukin (IL)-1β, IL-6, malondialdehyde (MDA) increased and superoxide dismutase (SOD) decreased as the PF cycle progressed. In the 1-, 2- and 4-week model group, 2, 19 and 18 potential metabolic biomarkers and 3, 16 and 12 potential microbial biomarkers were detected, respectively, which were significantly correlated. Glycerophospholipid metabolism pathway was observed to be an important pathway affecting PF at 1, 2 and 4 weeks; arginine and proline metabolism pathways significantly affected PF at 2 weeks. Linoleic acid metabolism pathway exhibited clear metabolic abnormalities at 2 and 4 weeks of PF, and alpha-linolenic acid metabolism pathway significantly affected PF at 4 weeks.

Abstract Background The caregiver contribution to self-care plays an important role in improving the health outcomes of chronic patients, which needs urgent attention. However, it has been hindered by the lack of a tailored instrument that assesses the caregiver contribution to self-care of stroke. Objectives To test the psychometric characteristics of the caregiver contribution to self-care of stroke Inventory (CC-SCSI) in health care practice. Methods Participants were recruited in Henan Province from March 2021 to October 2022, utilizing a multicenter stratified sampling approach. A 23-item self-report CC-SCSI with 3 separate scales measuring caregiver contribution to self-care maintenance of stroke, caregiver contribution to self-care monitoring of stroke and caregiver contribution to self-care management of stroke was tested for validity through discriminant validity, confirmatory factor analysis, concurrent validity and convergent validity. The reliability was tested by Cronbach’s α coefficient and test-retest reliability. Qualitative data were analysed using thematic analysis. A STROBE checklist was used. Results The three scales of the CC-SCSI exhibited good discriminant validity. Confirmatory factor analysis supported the three-factor structure of the Caregiver Contribution to Stroke Self-Care Maintenance and Management scales and the one-factor structure of the Caregiver Contribution to Stroke Self-Care Monitoring scale. The moderate correlation between the CC-SCSI and the Self-Care of Stroke Inventory indicated acceptable concurrent validity. The moderate correlation between the CC-SCSI and the Caregiver Contribution to Self-Care of Chronic Illness Inventory indicated acceptable convergent validity. Cronbach’s αs for the Caregiver Contribution to Self-Care Maintenance, Self-Care Monitoring, and Self-Care Management scales ranged from 0.876 to 0.974. Test-retest reliability showed average ICC values ranging from 0.828 to 0.903 (P

Aim: To compare the dosimetric advantages and disadvantages between hybrid intensity-modulated radiation therapy (h-IMRT) and the volumetric modulated arc therapy (VMAT) technique in hypofractionated whole-breast irradiation (HF-WBI) for early-stage breast cancer (BC). Methods: The dose distribution of h-IMRT and VMAT plans was compared in 20 breast cancer patients. This comparison included evaluation of dosimetric parameters using dose volume histograms (DVHs) for the planning target volume (PTV) and organs-at-risk (OARs). Additionally, the study examined the normal tissue complication probability (NTCP), the second cancer complication probability (SCCP) and the tumor control probability (TCP) based on different models. Results: Significant differences were detected between the two plans, in terms of Machine units (MUs), the control points, 95 % volume (V95 %), dose homogeneity index (DHI) and conformity index (CI). The endpoint of grade II radiation pneumonitis and cardiac death due to ischemic heart disease were assessed. In h-IMRT plan, the NTCP values were marginally lower for radiation pneumonitis and slightly higher for cardiac death compared to VMAT plan, as determined by the Lyman–Kutcher–Burman model. The Schneider model was employed to predict the SCCP for both the bilateral lungs and contralateral breast, the results demonstrate that the h-IMRT plan outperforms the VMAT plan, with statistical significance. Additionally, the LQ-Poisson model was employed to forecast the TCP of the PTV, showing that the h-IMRT plan outperformed the VMAT plan (P > 0.05). Conclusion: The h-IMRT technique, offering superior dose coverage and better therapeutic efficacy with fewer side effects as calculated by models, is more suitable for HF-WBI compared to the VMAT technique.

The coordinated development of green finance and technological innovation is a key driver of China's high-quality economic growth and therefore deserves close attention. But are green finance and technological innovation really coordinated? This study establishes a coordinating coupling system to link green finance and technological innovation. 2010–2021 is chosen as the observation period, and 31 provinces in China are selected for study. This paper uses the coupling coordination model to investigate the development of the coupling coordination of technological innovation and green finance, and discusses its spatial distribution by the Moran index. The results show that, overall, the degree of coupling coordination between green finance and technological innovation shows a consistent upward trend. The trend is particularly strong in the East. Moreover, the coordination coupling between green finance and technological innovation has the spatial effect. And it shows a binary characteristic, with a decreasing trend observed from coastal to inland regions. These results remained valid after replacing weight matrix and sample size.The above findings have important policy implications for optimising the synergistic development of green finance and technological innovation and achieving high-quality economic development.

Purpose: This study evaluated the first clinical implementation of daily iterative cone beam computed tomography (iCBCT)-guided online adaptive radiation therapy (oART) in the postoperative treatment of endometrial and cervical cancer. Methods and Materials: Seventeen consecutive patients treated with daily iCBCT-guided oART were enrolled in this prospective study, with a reduced uniform 3-dimensional PTV margin of 5 mm. Treatment plans were designed to deliver 45 or 50.4 Gy in 1.8 Gy daily fractions to PTV. Pre- and posttreatment ultrasound and iCBCT scans were performed to record intrafractional bladder and rectal volume changes. The accuracy of contouring, oART procedure time, dosimetric outcomes, and acute toxicity were evaluated. Results: The average time from first iCBCT acquisition to completion of treatment was 22 minutes and 26 seconds. During this period, bladder volume increased by 44 cm3 using iCBCT contouring, whereas rectal volume remained stable (62.9 cm3 pretreatment vs 61.9 cm3 posttreatment). A total of 91.6% of influencers and 88.1% of CTVs required no or minor edits. The adapted plan was selected in all (434) fractions and significantly improved the dosimetry coverage for CTV and PTV, especially the vaginal PTV coverage by nearly 7% (P < .05). The adapted bladder Dmean was 104.61 cGy, and the rectum Dmean was 123.67 cGy, significantly lower than the scheduled plan of 108.24 and 128.19 cGy, respectively. The bone marrow and femur head left and right dosimetry were also improved with adaptation. Grade 2 acute gastrointestinal and genitourinary toxicities were 24% and 0, respectively. There was a grade 3 acute toxicity of decreased white blood cell count in 1 patient. Conclusions: Daily oART was associated with favorable dosimetry improvement and low acute toxicity, supporting its safety and efficacy for postoperative treatment of endometrial and cervical cancer. These results need to be validated in a larger prospective randomized controlled cohort.

Abstract Background Small intestinal monomorphic–epitheliotropic intestinal T-cell lymphoma (MEITL) is a rare aggressive T-cell lymphoma originating in the gastrointestinal tract. This study aimed to investigate the clinicopathological features, immunophenotypes, and molecular genetic changes of MEITL. Methods The clinicopathological data for three patients with surgically resected MEITL of the small intestine were collected. Next, immunohistochemical labeling, Epstein–Barr virus (EBV) in situ hybridization, assessment of clonal rearrangement of T-cell receptor (TCR) genes, and next-generation sequencing (NGS) were performed. Results Of the three patients, two were male and one was female, with ages of 61, 67, and 73 years, respectively. Clinical manifestations were predominantly abdominal pain and distension. Histopathology revealed infiltrative growth of small-to-medium-sized lymphocytes with a consistent morphology between the intestinal walls, accompanied by an obvious pro-epithelial phenomenon. The expression of CD3, CD8, CD43, CD56, TIA-1, CD103, H3K36me3, and Bcl-2 was detected, and the Ki-67 proliferation index ranged from 50% to 80%. All three patients tested negative for EBER. However, monoclonal rearrangement of the TCR gene was detected in them. NGS testing showed a JAK3 mutation in all three cases. Further, STAT5B, SETD2, and TP53 mutations were each observed in two cases, and a BCOR mutation was found in one case. All patients were treated with chemotherapy after surgery. Two patients died 7 and 15 month post-operation, and one patient survived for 5 months of follow-up. Conclusions Our findings demonstrate that mutations in JAK3 and STAT5B of the JAK/STAT pathway and inactivation of the oncogene SETD2 markedly contribute to the lymphomagenesis of MEITL.

[Objective] In view of the increasing number of large-scale transfer stations in urban rail transit, which are characterized by deep burial depth, intensive personnel, limited escape and rescue sites, the difficulty and pressure of emergency and disaster prevention is very prominent. It is necessary to design the emergency and disaster prevention for such type of stations. [Method] With Optics Valley Plaza Complex in Wuhan as a practical case, the disaster characteristics faced by the large-scale transfer station are analyzed from five key aspects i.e. fire prevention, large passenger flow prevention, flood prevention, terrorist attack prevention and emergency epidemic protection. Solutions to the different types of disasters are proposed in combination with scheme design, simulation, calculation and analysis. [Result & Conclusion] Using open building layout and run-through pedestrian traffic layer, and setting up quasi-safety areas with natural smoke exhaust and sunken square are the effective fire prevention measures for the large underground space under difficult conditions. Analyzing the peak passenger flow based on the characteristics of the station, classifying the users of different types and in different periods, and setting up relatively independent and less crossover flow lines are the ways to effectively prevent large passenger flow. In addition to conventional flood prevention measures, strengthening hard isolation measures from surrounding underground spaces, such as adding flood doors, is a necessary means of flood prevention. Keeping the station clear, evacuating passengers quickly, and avoiding passengers′ stagnation can effectively prevent terrorist attacks. In response to sudden epidemics, daily prevention and control management should be strictly implemented in accordance with China′s relevant national regulations, and general or larger epidemic response measures should be taken in a timely manner.

Abstract Target detection based on hyperspectral images refers to the integrated use of spatial information and spectral information to accomplish the task of localization and identification of targets. There are two main methods for hyperspectral target detection: supervised and unsupervised methods. Supervision method refers to the use of spectral differences between the target to be tested and the surrounding background to identify the target when the target spectrum is known. In ideal situations, supervised object detection algorithms perform better than unsupervised algorithms. However, the current supervised object detection algorithms mainly have two problems: firstly, the impact of uncertainty in the ground object spectrum, and secondly, the universality of the algorithm is poor. A hyperspectral target detection framework based on 3D–2D CNN and transfer learning was proposed to solve the problems of traditional supervised methods. This method first extracts multi-scale spectral information and then preprocesses hyperspectral images using multiple spectral similarity measures. This method not only extracts spectral features in advance, but also eliminates the influence of complex environments to a certain extent. The preprocessed feature maps are used as input for 3D–2D CNN to deeply learn the features of the target, and then, the softmax method is used to output and obtain the detection results. The framework draws on the ideas of integrated learning and transfer learning, solves the spectral uncertainty problem with the combined similarity measure and depth feature extraction network, and solves the problem of poor robustness of traditional algorithms by model migration and parameter sharing. The area under the ROC curve of the proposed method has been increased to over 0.99 in experiments on both publicly available remote sensing hyperspectral images and measured land-based hyperspectral images. The availability and stability of the proposed method have been demonstrated through experiments. A feasible approach has been provided for the development and application of specific target detection technology in hyperspectral images under different backgrounds in the future.

Abstract T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive subtype of ALL characterized by its high heterogeneity and unfavorable clinical features. Despite improved insights in genetic and epigenetic landscapes of T-ALL, the molecular mechanisms that drive malignant T-cell development remain unclear. BTB and CNC homology 2 (BACH2) is a lymphoid-specific transcription repressor recognized as a tumor suppressor in B-cell malignancies, but little is known about its function and regulatory network in T-ALL. Here we found extremely low levels of BACH2 in T-ALL clinical samples and cell lines compared to normal T cells. Overexpression of BACH2 in T-ALL cells not only induced cell growth retardation but also inhibited cancer progression and infiltration in xenografts. Further RNA sequencing (RNA-seq) analysis revealed significant alterations in regulation of defense and immune responses in T-ALL cells upon BACH2 overexpression. Strikingly, CD28 and CD40LG, two essential stimulatory molecules on T cells, were for the first time identified as novel downstream targets repressed by BACH2 in T-ALL cells. Interestingly, both CD28 and CD40LG were indispensable for T-ALL survival, since largely or completely silencing CD28 and CD40LG led to rapid cell death, whereas partial knockdown of them resulted in cell-cycle arrest and enhanced apoptosis. More importantly, BACH2-mediated CD28 and CD40LG signals contributed to cell migration and dissemination of T-ALL cells to the bone marrow, thus adding a new layer to the BACH2-mediated tumor immunoregulation in T-cell malignancies.

Background Creatine supplementation is ubiquitously consumed by fitness enthusiasts due to its perceived advantages in enhancing athletic performance. Although there is an increasing concern within this demographic regarding its possible impact on renal function, there is still a lack of rigorous scientific investigations into this alleged association.Methods Data were collected through an online survey on the participants’ demographics, creatine usage and concerns related to renal function. The reliability and validity of the survey were assessed using SPSS software. A total of 1129 participants responded to the survey, and chi-square tests were utilized for data analysis. To explore the potential association between creatine levels (as the exposure) and renal function (as the outcome), we utilized open-access genetic databases, and Mendelian randomization (MR) techniques were used to confirm this correlation.Results Chi-square analysis revealed no significant association between creatine usage and renal function among the participants. Our MR analysis further supported this finding, demonstrating no significant association between creatine levels and six indicators assessing renal function (IVW, all with p values exceeding 0.05). Similar p values were consistently observed across other MR methods, confirming the absence of a statistical correlation.Conclusions This MR study offers compelling evidence indicating that creatine levels are not statistically associated with renal function, suggesting the potential to alleviate concerns within the fitness community and emphasizing the significance of evidence-based decision-making when considering nutritional supplementation.

Men who have sex with men and people living with HIV are disproportionately affected in the 2022 multi-country monkeypox epidemic. The smallpox vaccine can induce cross-reactive antibodies against the monkeypox virus (MPXV) and reduce the risk of infection. Data on antibodies against MPXV induced by historic smallpox vaccination in people with HIV are scarce. In this observational study, plasma samples were collected from people living with and without HIV in Shenzhen, China. We measured antibodies binding to two representative proteins of vaccinia virus (VACV; A27L and A33R) and homologous proteins of MPXV (A29L and A35R) using an enzyme-linked immunosorbent assay. We compared the levels of these antibodies between people living with and without HIV. Stratified analyses were performed based on the year of birth of 1981 when the smallpox vaccination was stopped in China. Plasma samples from 677 people living with HIV and 746 people without HIV were tested. A consistent pattern was identified among the four antibodies, regardless of HIV status. VACV antigen-reactive and MPXV antigen-reactive antibodies induced by historic smallpox vaccination were detectable in the people born before 1981, and antibody levels reached a nadir during or after 1981. The levels of smallpox vaccine-induced antibodies were comparable between people living with HIV and those without HIV. Our findings suggest that the antibody levels against MPXV decreased in both people living with and without HIV due to the cessation of smallpox vaccination.

AbstractIn this study, UV-B radiation of 96 kJ·m−2·d−1 exposed to the ‘Tainong 1’ mango tree, and trees as the control group under natural lighting. The relative conductivity and the contents of MDA, superoxide anion, H2O2 were lower in the treatment group than in the control group before 60 DAF, and the opposite occurred after 60 DAF. The total flavonoid content in the treatment group was higher than that in the control group, but the opposite occurred later. The 60 DAF serves as the critical point. Before 60 DAF, the treatment enhanced the activity of each enzyme by inducing the upregulated expression of genes such as CHS, R02446, and CYP98A so that gallochol, leucoside, kaempferoside, quercetin, isoquercetin and luteolin, and then removed ROS through the reduction of flavonoids. After 60 DAF, the treatment enhanced the activity of each enzyme by inducing the upregulated expression of HCT and R02446, but the synthesized flavonoids are consumed by ROS. Meanwhile, ROS also accumulate continuously because of the enhanced continuous exposure of UV-B radiation. The downregulated expression of CYP75A led to a decline in enzyme activity. The accumulation rate of flavonoid compounds was lower than that of ROS, which led to ROS damage in pulp.

The fascial space of the oral and maxillofacial region contains loose connective tissues, which possess weak anti-infection ability and are often prone to infection, leading to acute suppurative inflammation and sepsis through blood. Although antibiotic use can reduce the probability of bacterial infections, owing to the emergence of antibiotic-resistant bacteria, the search for new antimicrobial drugs is imminent. Herein, we report a metal–organic framework (MOF) antibacterial material designed and synthesized with gallium (Ga) as the central atom, which possesses significant antibacterial, anti-inflammatory, and antioxidant effects. Our data suggested that GA-based MOFs (Ga–MOFs; 1 μg/mL) could sufficiently kill Porphyromonas gingivalis, Streptococcus pyogenes, and Staphylococcus aureus. Ga–MOFs exhibited a bactericidal effect against these three pathogens by disrupting biofilm formation, exopolysaccharide production, and bacterial membrane integrity. In addition, we found that 1 μg/mL of Ga–MOFs was not cytotoxic to human oral epithelial cell (HOEC) lines and it significantly reduced the adhesion of the three pathogens to HOEC. Ga–MOFs protect macrophages from excessive oxidative stress by scavenging excess intracellular reactive oxygen species and upregulating antioxidant gene levels, thereby enhancing cellular antioxidant defense. In addition, Ga–MOFs can promote the transformation of macrophages from the proinflammatory phenotype to the anti-inflammatory phenotype, thereby protecting oral health. Herein, novel Ga–MOF materials were chemically synthesized for therapeutic applications in oral infections, which provides new ideas for the development of novel nonantibiotic drugs to accelerate patient recovery.

Cases of mixed neuroendocrine-non-neuroendocrine neoplasms (MiNENs) of the urinary system are rare, and reports of primary MiNENs in the ureter are lacking. Herein, we present the case of a 71-year-old man who presented with painless gross hematuria and weight loss. Contrast-enhanced abdominal computed tomography (CT) revealed a tumor, comprising small cell neuroendocrine carcinoma (SCNEC) and adenocarcinomatous components, attached to the ureter. The SCNEC components were strongly positive for synaptophysin, CD56 and INSM1 and adenocarcinomatous components were strongly positive for CDX2 and cytokeratin 20, respectively. Four weeks post-surgery, the patient received four cycles of cisplatin-based chemotherapy; the 7-month follow-up CT confirmed that he was healthy without disease recurrence. The occurrence of MiNEN in the ureter with SCNEC and adenocarcinomatous components is extremely rare, wherein histopathological and immunohistochemical features aid in the diagnosis MiNEN. With its aggressive nature, MiNEN can only be effectively treated by early diagnosis and radical surgery.

To address global climate change and achieve high-quality development, China has to reach carbon peaking and carbon neutrality targets as objective requirements. Based on data from 30 Chinese provinces from 2011 to 2021, this study used a two-factor fixed effects and a mechanism model to test the effects and mechanisms of digital finance on carbon performance. The findings imply that the development of digital finance has a nonlinear effect of the ''first inhibit, then promote'' principle on carbon performance. Meanwhile, both the coverage breadth and usage depth of digital finance have a more significant impact on carbon performance. Digital financing can improve regional carbon performance through green technology innovation, industrial upgrades, and energy structure optimization. In addition, this effect exhibited significant heterogeneity. Specifically, the higher the level of marketization and the lower the urban–rural income gap, the more significant the nonlinear effect. The eastern region has the advantage of being rich in resources and technology, and the effect in the eastern region is more obvious compared to central and western regions. Therefore, China should accelerate the integration of financial services with modern digital technologies to achieve low-carbon development based on local conditions.

The source area of the Yellow River (SAYR), located above the Huangheyan hydrological station, is important for ecological preservation and water source conservation in the Yellow River Basin. In this area, the impact of water conservation projects on the hydrology and the ecological environment is pivotal in protecting water resources and alpine vegetation ecosystems. This study investigates the impact of the Yellow River Source Hydropower Station on the runoff and ecological evolution of the SAYR, along with the underlying mechanism, using extensive datasets encompassing long-term meteorological, hydrological and remote sensing data from various time periods. Results show that, over the long term, precipitation is the primary factor driving runoff variations in the SAYR. Nevertheless, from 1990 to 2020, there is a notably inconsistent relationship between precipitation and runoff. After the completion of the Yellow River Source Hydropower Station in 2001, the water level of Eling Lake experienced and elevation of 2–3 m, leading to a gradual recovery of runoff. In addition, the basin's water balance shifted from a negative to a positive equilibrium, oscillating with changes in lake water levels. Consequently, the overflow zone of the Tangchama alluvial–proluvial fan in the upper reaches of the lakeshore shifted by 500 m, and marsh wetlands expanded by 20.78 km2. The increased storage of lakes and groundwater in the SAYR is the key controlling factor for the runoff recovery, changes in the basin's water balance, and enhancements in lakeshore vegetation ecology. Under the geological background of the Qinghai–Tibet Plateau's upliftment and intensified upstream river erosion, the basin experienced a substantial water imbalance due to declining discharge base levels, which is the most critical factor behind runoff attenuation in the SAYR towards the end of the 20th century. The construction of the hydropower station objectively raised the drainage base level of the basin, thereby positively contributing to the preservation of water balance, runoff stability, and the enhancement of swamps and wetlands along the lakeshore.

Abstract In land-based spectral imaging, the spectra of ground objects are inevitably affected by the imaging conditions (weather conditions, atmospheric conditions, light conditions, zenith and azimuth angle conditions) and spatial distribution of targets, leading to uncertainties featured by “same object different spectrum”. That is, the spectrum of a ground object may change within a certain range under different imaging conditions. Traditional target detection (TD) methods are mainly based on similarity measurements and do not fully account for the spectral uncertainties. These detection methods are prone to false detections or missed detections. Therefore, reducing the impact of spectral uncertainties on TD is an important research topic in hyperspectral imaging. In this paper, we first review traditional TD methods and compare their principles and characteristics. It is found that the spectral correlation angle (SCA) method has good adaptability in land-based imaging. The shortcoming of the SCA method that it cannot reflect the local spectrum characteristics, is also analyzed. As the effect of spectral uncertainties cannot be completely overcome by the SCA method, a new similarity measurement method, the weighted spectral correlation angle (WSCA) method, is proposed. It can reduce the influence of spectral uncertainties on TD by increasing the weight of particular bands. Finally, we use two sets of experiments to analyze the effect of the WSCA method on TD. Its performance in overcoming spectral uncertainties caused by variations in imaging conditions or uneven spatial distributions of targets is tested. The results show that the WSCA method can effectively reduce the influence of spectral uncertainties and obtain a good detection result. Graphical Abstract

Abstract Background The rapid reproduction of malaria parasites requires proper iron uptake. However, the process of iron absorption by parasites is rarely studied. Divalent metal transporter (DMT1) is a critical iron transporter responsible for uptaking iron. A homolog of human DMT1 exists in the malaria parasite genome, which in Plasmodium yoelii is hereafter named PyDMT1. Results PyDMT1 knockout appears to be lethal. Surprisingly, despite dwelling in an iron-rich environment, the parasite cannot afford to lose even partial expression of PyDMT1; PyDMT1 hypomorphs were associated with severe growth defects and quick loss of pathogenicity. Iron supplementation could completely suppress the defect of the PyDMT1 hypomorph during in vitro culturing. Genetic manipulation through host ferritin (Fth1) knockout to increase intracellular iron levels enforced significant growth inhibition in vivo on the normal parasites but not the mutant. In vitro culturing with isolated ferritin knockout mouse erythrocytes completely rescued PyDMT1-hypomorph parasites. Conclusion A critical iron requirement of malaria parasites at the blood stage as mediated by this newly identified iron importer PyDMT1, and the iron homeostasis in malarial parasites is finely tuned. Tipping the iron balance between the parasite and host will efficiently kill the pathogenicity of the parasite. Lastly, PyDMT1 hypomorph parasites were less sensitive to the action of artemisinin.

Endocrine-resistance remains a major challenge in estrogen receptor α positive (ERα+) breast cancer (BC) treatment and constitutively active somatic mutations in ERα are a common mechanism. There is an urgent need to develop novel drugs with new mode of mechanism to fight endocrine-resistance. Given aberrant ERα activity, we herein report the identification of novel covalent selective estrogen receptor degraders (cSERDs) possessing the advantages of both covalent and degradation strategies. A highly potent cSERD 29c was identified with superior anti-proliferative activity than fulvestrant against a panel of ERα+ breast cancer cell lines including mutant ERα. Crystal structure of ERα‒29c complex alongside intact mass spectrometry revealed that 29c disrupted ERα protein homeostasis through covalent targeting C530 and strong hydrophobic interaction collied on H11, thus enforcing a unique antagonist conformation and driving the ERα degradation. These significant effects of the cSERD on ERα homeostasis, unlike typical ERα degraders that occur directly via long side chains perturbing the morphology of H12, demonstrating a distinct mechanism of action (MoA). In vivo, 29c showed potent antitumor activity in MCF-7 tumor xenograft models and low toxicity. This proof-of-principle study verifies that novel cSERDs offering new opportunities for the development of innovative therapies for endocrine-resistant BC.

Extracting precise geographical information from the textual content, referred to as toponym recognition, is fundamental in geographical information retrieval and crucial in a plethora of spatial analyses, e.g. mining location-based information from social media, news reports, and surveys for various applications. However, the performance of existing toponym recognition methods and tools is deficient in supporting tasks that rely on extracting fine-grained geographic information from texts, e.g. locating people sending help requests with addresses through social media during disasters. The emerging pretrained language models have revolutionized natural language processing and understanding by machines, offering a promising pathway to optimize toponym recognition to underpin practical applications. In this paper, TopoBERT, a uniquely designed toponym recognition module based on a one-dimensional Convolutional Neural Network (CNN1D) and Bidirectional Encoder Representation from Transformers (BERT), is proposed and fine-tuned. Three datasets are leveraged to tune the hyperparameters and discover the best strategy to train the model. Another seven datasets are used to evaluate the performance. TopoBERT achieves state-of-the-art performance (average f1-score = 0.854) compared to the seven baseline models. It is encapsulated into easy-to-use python scripts and can be seamlessly applied to diverse toponym recognition tasks without additional training.

The supra-permafrost water is a vital water source to support the ecosystem and an important link in maintaining the hydrothermal cycle in the permafrost area. Under the intensification of climate change, scientific understanding of the effect of permafrost degradation on the supra-permafrost water is of great significance to water resources and ecological protection. Focusing on the hydrological effects of permafrost degradation in the source areas of the Yellow River, this study analyzed the degradation characteristics of permafrost, and revealed the response of the depth of groundwater level and recharge process of the supra-permafrost water to the permafrost degradation, on the basis of the temperature and moisture content of frozen soil at typical monitoring points and the runoff change at the Huangheyan Hydrologic Station. The results show that the average temperature increased 0.42 °C at the 0−2.4 m profile of the monitoring point from 2010 to 2020. The depth of the upper interface of the permafrost reduced from 2.1m to 2.5 m, with an average decrease rate of 4cm/a. After 2018, the depth of supra-permafrost water level reduced from less than 0.9 m to 0.9−1.8 m. The permafros degradation led to the runoff process in the melting period of active layer (May−October) being advanced, the ratio of extreme value being reduced，and the runoff hydrograph in January being more prominent. Ground temperature is the dominant factor in controlling the changes of depth of the supra-permafrost water. Under the condition of warm and humid climate change, Permafrost degradation would change the dynamic characteristics of the water above the frozen layer and its hydraulic relationship with surface water, affecting the hydrological and ecological processes in the source area of the Yellow River.

In order to meet the demand of the intelligent and efficient picking of fresh citrus fruit in a natural environment, a flexible and independent picking method of fresh citrus fruit based on picking pattern recognition was proposed. The convolutional attention (CA) mechanism was added in the YOLOv7 network model. This makes the model pay more attention to the citrus fruit region, reduces the interference of some redundant information in the background and feature maps, effectively improves the recognition accuracy of the YOLOv7 network model, and reduces the detection error of the hand region. According to the physical parameters of the citrus fruit and stem, an end-effector suitable for picking citrus fruit was designed, which effectively reduced the damage during the picking of citrus fruit. According to the actual distribution of citrus fruits in the natural environment, a citrus fruit-picking task planning model was established, so that the adaptability of the flexible handle can make up for the inaccuracy of the deep learning method to a certain extent when the end-effector picks fruits independently. Finally, on the basis of integrating the key components of the picking robot, a production test was carried out in a standard citrus orchard. The experimental results show that the success rate of the citrus-picking robot arm is 87.15%, and the success rate of picking in the natural field environment is 82.4%, which is better than the success rate of 80% of the market picking robot. In the picking experiment, the main reason for the unsuccessful positioning of citrus fruits is that the position of citrus fruits is beyond the picking range of the end-effector, and the motion parameters of the robot arm joint will produce errors, affecting the motion accuracy of the robot arm, leading to the failure of picking. This study can provide technical support for the exploration and application of the intelligent fruit-picking mode.

The porous media approach is regarded as an appropriate methodology for hydraulic simulations of complex pebble beds in fusion reactors. In order to determine the parameters (permeability α and inertial loss coefficient C) of the porous media accurately, two methods are proposed: the correction method and the fitting method. In this paper, a single-channel model with sequentially packed pebbles is constructed in order to obtain the pressure drop gradient against superficial velocities. Two methods, the correction method and fitting method, are employed to determine the permeability and inertial loss coefficient, and the results are evaluated with comparisons. Based on the results, both the correction method and fitting method are deemed feasible for the parameter determinations. In consideration of the consumption of resources and time for simulation, the fitting method is recommended during the preliminary design phase to shorten the duration of design, while the correction method is suggested to obtain precise results when the design is accomplished. Both of the methods would be evaluated with the data obtained from experiments in the future.

The lack of spatial pose information and the low positioning accuracy of the picking target are the key factors affecting the picking function of citrus-picking robots. In this paper, a new method for automatic citrus fruit harvest is proposed, which uses semantic segmentation and rotating target detection to estimate the pose of a single culture. First, Faster R-CNN is used for grab detection to identify candidate grab frames. At the same time, the semantic segmentation network extracts the contour information of the citrus fruit to be harvested. Then, the capture frame with the highest confidence is selected for each target fruit using the semantic segmentation results, and the rough angle is estimated. The network uses image-processing technology and a camera-imaging model to further segment the mask image of the fruit and its epiphyllous branches and realize the fitting of contour, fruit centroid, and fruit minimum outer rectangular frame and three-dimensional boundary frame. The positional relationship of the citrus fruit to its epiphytic branches was used to estimate the three-dimensional pose of the citrus fruit. The effectiveness of the method was verified through citrus-planting experiments, and then field picking experiments were carried out in the natural environment of orchards. The results showed that the success rate of citrus fruit recognition and positioning was 93.6%, the average attitude estimation angle error was 7.9°, and the success rate of picking was 85.1%. The average picking time is 5.6 s, indicating that the robot can effectively perform intelligent picking operations.

This paper introduces a novel approach to attain the shot-noise limit in laser frequency-shift feedback (LFSF) imaging systems by employing a polarization-modulated optical loop. Compared to the traditional LFSF imaging system, the proposed system effectively eliminates detrimental parasitic feedback signals, enhancing both the signal-to-noise ratio and the response range of the LFSF imaging system. Specifically, in the polarization-modulated optical loop, only the measurement light propagating through the loop undergoes efficient modulation, while the parasitic feedback light experiences high-frequency modulation beyond the bandwidth of the photodetector. Experimental findings demonstrate the superiority of our proposed system over traditional LFSF imaging systems in the insensitivity of parasitic feedback, showcasing a higher signal-to-noise ratio and response range. Moreover, the proposed system achieved a distinctive polarization imaging technique, which exhibits the capability to discern and analyze the distinct specular reflection and depolarized scattering components in the measurement light, thus providing more comprehensive target information.

The Weihe Basin, located in central China, stands out for its significant earthquake activity while concurrently harboring promising geothermal reservoirs. The potential association between these two geological occurrences and the underlying mechanisms remain enigmatic. Here, we compile a catalog of historic earthquakes, total strain data, data related to crustal mantle structure, surface heat flow data, and heat production data of the rocks in the Weihe Basin. Our aim is to unveil the intricate interplay among the occurrence of earthquakes, tectonic activity, and the genesis of geothermal resources. Our findings reveal that earthquake activity in the Weihe Basin is regulated by the responses of faults or fractures intricately influenced by regional tectonics. These tectonic processes are responsible for the formation of favorable geothermal resources beneath the basin. We propose there is a weak zone beneath the basin, which is controlled by a combination of tectonic processes and the flow of the asthenosphere. We finally establish a comprehensive model to visualize the genesis of the occurrence of earthquakes and the formation of geothermal resources. These results have important guiding significance for future research endeavors in the realms of both geothermal exploration and earthquake investigations within the Weihe Basin.

Summary: Background: Frail elderly patients with newly diagnosed multiple myeloma (NDMM) have inferior survival and less benefit from high-dose therapies. This prospective study aimed to investigate the efficacy, safety, and quality of life (QoL) of induction treatment of ixazomib/lenalidomide/dexamethasone (IRd) and ixazomib/pegylated liposomal doxorubicin/dexamethasone (IDd) followed by ixazomib/dexamethasone (Id) maintenance therapy in frail, elderly patients with NDMM. Methods: From July 2019 to December 2021, this non-randomized concurrent controlled clinical study enrolled 120 NDMM patients aged ≥65 years with frailty defined by the International Myeloma Working Group (IMWG) frailty score or Mayo geriatric scoring system. The enrolled patients received 6–8 cycles of IRd or IDd followed by Id maintenance therapy for a minimum of 2 years at the discretion of physicians based on patient's clinical characteristics (chiCTR1900024917). Findings: The median age was 71 years and 55% of the patients were males. The overall response rate (ORR) was 82% and 77%, complete response (CR) rate was 25% and 12% for IRd and IDd groups, respectively. The difference in ORR of the Idd group minus the IRd group was −5.36% (95% CI: −18.9% to 8.19%), indicating that the ORR of the IDd group was neither inferior nor non-inferior to the IRd group. After a median follow-up of 34.3 months, the median progression-free survival (PFS) was 21.6 and 13.9 months, OS was not reached and 29.2 months in IRd and IDd groups, respectively. 28 and 33 patients discontinued induction therapy, 20 and 19 discontinued maintenance therapy in IRd and IDd groups, respectively. Cumulative Grade 3 or higher hematological adverse events (AEs) occurred in 10 of the 60 patients (17%) and non-hematological AEs occurred in 15 of the 60 patients (25%) in the IRd group, while 13 of the 60 patients (22%) and 21 of the 60 patients (35%) in the IDd group. Patients were observed with clinically significant improvement in QoL when compared with that at baseline in both IRd and IDd groups by evaluation per cycle (P