The OsZIP2 transporter is involved in root-to-shoot translocation and intervascular transfer of cadmium in rice.

Cadmium (Cd) is a toxic metal that poses serious threats to human health. Rice is a major source of dietary Cd but how rice plants transport Cd to the grain is not fully understood. Here, we characterize the function of the ZIP (ZRT, IRT-like protein) family protein, OsZIP2, in the root-to-shoot translocation of Cd and intervascular transfer of Cd in nodes. OsZIP2 is localized at the plasma membrane and exhibited Cd2+ transport activity when heterologously expressed in yeast. OsZIP2 is strongly expressed in xylem parenchyma cells in roots and in enlarged vascular bundles in nodes. Knockout of OsZIP2 significantly enhanced root-to-shoot translocation of Cd and alleviated the inhibition of root elongation by excess Cd stress; whereas overexpression of OsZIP2 decreased Cd translocation to shoots and resulted in Cd sensitivity. Knockout of OsZIP2 increased Cd allocation to the flag leaf but decreased Cd allocation to the panicle and grain. We further reveal that the variation of OsZIP2 expression level contributes to grain Cd concentration among rice germplasms. Our results demonstrate that OsZIP2 functions in root-to-shoot translocation of Cd in roots and intervascular transfer of Cd in nodes, which can be used for breeding low Cd rice varieties.

[Construction and Analysis of Machine Learning Based Transportation Carbon Emission Prediction Model].

Addressing the issue of carbon emissions in the transportation sector, this research constructed various predictive models using multiple machine learning algorithms based on panel data from 30 provinces in China from 2005 to 2019. The study aimed to identify the optimal machine learning algorithm and key factors influencing the carbon emissions of transportation, providing potent references for policymakers and decision-makers to reduce carbon emissions and promote the sustainable development of the transportation sector. Initially, drawing from the concept of the fixed effects model, we included the heterogeneity differences among provinces as an important factor. We further employed a combined method of Pearson's correlation coefficient and Spearman's rank correlation coefficient to screen 18 factors influencing transportation carbon emissions. We then made a preliminary selection of seven common machine learning algorithms and used the screened factors as explanatory variables for model training. The three algorithms with the best performance were further optimized and trained. Subsequently, we utilized the K-fold cross-validation method; plotted learning curves to test the performance of each predictive model; and used MSE, MAE, R2, and MAPE as evaluation indicators to determine the best predictive model. SHAP values were chosen to calculate the importance of each explanatory variable in the optimal predictive model. The results indicated that the multicollinearity among the seven factors of provincial differences, total consumption of social goods, urban green space area, freight turnover, number of private cars, transportation industry output, and permanent population was weak, and all passed the significance test. They could be used as explanatory variables in the prediction model of transportation carbon emissions. The prediction results of the Random Forest and XGBoost algorithms were both outstanding, with R2 values above 0.97 and errors below 10 %, showing no signs of overfitting or underfitting. Among them, the XGBoost algorithm performed the best, whereas the KNN algorithm performed poorly. The importance ranking of the explanatory variables was as follows:provincial differences > total consumption of social goods > number of private cars > permanent population > freight turnover > urban green space area > transportation industry output. A comprehensive analysis of relevance and importance showed that provincial differences were an indispensable variable in the prediction of transportation carbon emissions. In conclusion, this study provides a new approach to the governance of carbon emissions in the transportation industry, and the results can serve as a reference for policymakers and decision-makers. In future policy design and decision-making, the distinctive factors of each province should not be overlooked. Measures targeted at specific regions need to be formulated to promote the sustainable development of the transportation industry.

HIPTox-Hazard Identification Platform to Assess the Health Impacts from Indoor and Outdoor Air Pollutant Exposures, through Mechanistic Toxicology: A Single-Centre Double-Blind Human Exposure Trial Protocol.

Over the past decade, our understanding of the impact of air pollution on short- and long-term population health has advanced considerably, focusing on adverse effects on cardiovascular and respiratory systems. There is, however, increasing evidence that air pollution exposures affect cognitive function, particularly in susceptible groups. Our study seeks to assess and hazard rank the cognitive effects of prevalent indoor and outdoor pollutants through a single-centre investigation on the cognitive functioning of healthy human volunteers aged 50 and above with a familial predisposition to dementia. Participants will all undertake five sequential controlled exposures. The sources of the air pollution exposures are wood smoke, diesel exhaust, cleaning products, and cooking emissions, with clean air serving as the control. Pre- and post-exposure spirometry, nasal lavage, blood sampling, and cognitive assessments will be performed. Repeated testing pre and post exposure to controlled levels of pollutants will allow for the identification of acute changes in functioning as well as the detection of peripheral markers of neuroinflammation and neuronal toxicity. This comprehensive approach enables the identification of the most hazardous components in indoor and outdoor air pollutants and further understanding of the pathways contributing to neurodegenerative diseases. The results of this project have the potential to facilitate greater refinement in policy, emphasizing health-relevant pollutants and providing details to aid mitigation against pollutant-associated health risks.

Construction and optimization of ecological networks based on future scenario simulation in Qianshan City, Anhui Province.

The rapid urbanization adversely affects landscape pattern of mountainous cities. It is of great practical significance to explore the spatial and temporal evolution of ecological networks in mountainous areas to achieve regional ecological security. Taking Qianshan City in Anhui Province as an example, based on the land use data in 2012 and 2020, we simulated the land use situation in 2036 with PLUS model, and constructed the ecological networks in 2020 and 2036, respectively. We further analyzed its spatial and temporal evolution characteristics and explored the optimization path of ecological network. The results showed that the scale of various land use types in Qianshan City would change little from 2020 to 2036. The construction land would be centered on the built-up area, expanding in a point and block shape to the surrounding area. The ecological space would be continuously squeezed and encroached. The overall complexity and connectivity of ecological networks in Qianshan City would increase. The number and area of ecological source sites would increase, expanding spatially to the southwest and northeast. The overall density and number of ecological corridors would increase, with a lack of ecological corridor connections in the east-west direction, which need urgent improvement. The stability of ecological networks could be improved through three major measures, including protection and restoration of source sites, optimization and cultivation of corridors, and zoning control.

Combination of direct boiling and glass beads increases the purity and accuracy of bacterial DNA extraction.

Extraction of DNA is a key step in molecular biology experiments and important for counting tiny microbial individuals. Direct boiling and mechanical cell lysis like glass beads are two independent physical extraction methods, thus crossing the barriers of thresholds of magnitude in popular reagent kits or traditional spread plate method when non-equilibrium phenomenon is ongoing. The two approaches above were combined to generate a new one. In three typical microbial species, direct boiling with glass beads significantly increased the purity of DNA solution compared with some other methods (p < 0.05). The qPCR results of them were closer to direct microscopy counting than some other methods. Therefore, it provides a new choice in extracting bacterial DNA for specific circumstances.

Kinetic model derivation for design, building and operation of solid waste treatment unit based on system dynamics and computer simulation.

Solid waste disposal is significantly important to maintaining normal operation of both natural and artificial ecosystems. In this study, a kinetic model of solid waste treatment unit (SWTU) was upfront developed based on microbial ecology, system dynamics, cybernetics and digital simulation, which accurately described the relationships and interactions between solid waste decomposition (SWD) processes and biotic/abiotic factors. Then a specific SWTU prototype was designed and built from this kinetic model. A 370-day experiment demonstrated that SWTU maintained normal operation with robust stability and desired dynamic behaviors, and effectively disposed the solid waste. Therefore, this kinetic model was highly valid due to its high structural and behavioral similarity with the prototype. This research could lay a strong theoretical foundation for further closed-loop control as well as optimization of SWTU, and provide scientific guidance to environmental management as well as sustainable development.

Flexible Miniaturized Multispectral Detector Derived from Blade-Coated Organic Narrowband Response Unit Array.

Multispectral sensing is extremely desired in intelligent systems, e.g., autonomous vehicles, encrypted information communication, and health biometric monitoring, due to its highly sensitive spectral discrimination ability. Nevertheless, rigid bulky optics and delicate optical paths in devices significantly increase their complexity and size, which subsequently impede their integration in smart optoelectronic chips for universal applications. In this work, a filterless miniaturized multispectral photodetector is realized with an organic narrowband response unit array. With the manipulation of Frenkel exciton dissociation in active layers, a series of narrowband organic sensing units with full-width-at-half-maximum (fwhm) narrowing to ∼50 nm are achieved from 700 to 1050 nm with a laudable performance of responsivity of over 60 mA/W, -3 dB bandwidth over 10 kHz, linear dynamic range (LDR) reaching ∼120 dB, and a low noise current of less than 4 × 10-14 A·Hz-0.5. Furthermore, a 6 × 8 multispectral sensing array on a flexible substrate was fabricated with blade-coating. Assisted by a computational process, we successfully demonstrate the spectral recognition with a resolution of ∼50 nm and a mismatch of ∼10 nm. Finally, the function of matter identification is successfully achieved with our multispectral detector array.

Exhaust and non-exhaust airborne particles from diesel and electric buses in Xi'an: A comparative analysis.

Switching diesel buses (DBs) to electric buses (EBs) has been a global trend to reduce the use of fossil fuels and improve air quality. However, buses electrification may lead to additional vehicle weight, which may emit more non-exhaust particulate matter (PM) emissions. It remains debatable whether buses' electrification will successfully improve air quality as excepted. To assess the effect of the buses' electrification on the levels of PM emissions, PM emission factors (EFs) were evaluated from EBs and equivalent DBs. In addition, the total mass of PM emissions from EBs and equivalent DBs in 2021 was calculated in Xi'an using the real-world number and mileage of EBs. The non-exhaust PM EFs from EBs were larger than total exhaust and non-exhaust PM EFs from DBs, indicating that the electrification of buses would cause an increase in the level of PM emissions. The total annual mass of PM emissions from EBs was apparently higher than that from DBs. Moreover, a sensitivity analysis showed that tire wear, brake wear, and road wear PM emissions were more reliant on vehicle mileage, whereas resuspension of road dust was more dependent on vehicle weight. This finding can serve as a guideline for policymakers to design mitigation strategies for reducing extra PM emissions due to the electrification of buses by reasonably reducing vehicle weight and annual mileage.

Monolithic RGB-NIR Perovskite Photodetector for Fused Multispectral Sensing and Imaging.

The multispectral fusion of near-infrared (NIR) and visible red-green-blue (RGB) photons can enhance target identification under weak light conditions. Nevertheless, the crosstalk between NIR and RGB photons in a traditional pixelated sensor impedes their practical application, while using complex algorithms and optical filters would significantly increase the cost, form factor, and frame latency. In this work, a delicate monolithic RGBN (RGB-NIR) multispectral photodetector (PD) is proposed on the basis of perovskite materials without complicated algorithms or optical filters. The multispectral response toward selective RGBN signals in this monolithic PD pixels can be achieved by switching the polarity of the applied bias, affording the following benefits: Ion/Ioff ratio of >104, detectivity of >1010 Jones, crosstalk of -74 dB, and fast response with -3 dB > 103 Hz. Moreover, proof-of-concept imaging of the iris and periocular with successful recognition in multispectral fusion further confirms its potential for identity authentication.

Ammonium Chloride Associated Aerosol Liquid Water Enhances Haze in Delhi, India.

The interaction between water vapor and atmospheric aerosol leads to enhancement in aerosol water content, which facilitates haze development, but its concentrations, sources, and impacts remain largely unknown in polluted urban environments. Here, we show that the Indian capital, Delhi, which tops the list of polluted capital cities, also experiences the highest aerosol water yet reported worldwide. This high aerosol water promotes secondary formation of aerosols and worsens air pollution. We report that severe pollution events are commonly associated with high aerosol water which enhances light scattering and reduces visibility by 70%. Strong light scattering also suppresses the boundary layer height on winter mornings in Delhi, inhibiting dispersal of pollutants and further exacerbating morning pollution peaks. We provide evidence that ammonium chloride is the largest contributor to aerosol water in Delhi, making up 40% on average, and we highlight that regulation of chlorine-containing precursors should be considered in mitigation strategies.

Enhanced room-temperature terahertz detection and imaging derived from anti-reflection 2D perovskite layer on MAPbI3 single crystals.

Terahertz (THz) detection technology is getting increasing attention from scientists and industries alike due to its superiority in imaging, communication, and defense. Unfortunately, the detection of THz electromagnetic waves under room temperature requires a complicated device architecture design or additional cryogenic cooling units, which increase the cost and complexity of devices, subsequently imposing an impediment in its universal application. In this work, THz detectors operated under room temperature are designed based on the thermoelectric effect with MAPbI3 single crystals (SCs) as active layers. With solution-processed molecular growth engineering, the anti-reflection 2D perovskite layers were constructed on SCs' surfaces to suppress THz reflection loss. Simultaneously, by finely regulating the main carrier types and the direction of the applied bias across the inclined energy level, the thermoelectric effect is further promoted. As a result, THz-induced ΔT in MAPbI3 SCs reaches 4.6 °C, while the enhancement in the bolometric and photothermoelectric effects reach ∼4.8 times and ∼16.9 times, respectively. Finally, the devices achieve responsivity of 88.8 µA W-1 at 0.1 THz under 60 V cm-1, noise equivalent power (NEP) less than 2.16 × 10-9 W Hz-1/2, and specific detectivity (D*) of 1.5 × 108 Jones, which even surpasses the performance of state-of-the-art graphene-based room-temperature THz thermoelectric devices. More importantly, proof-of-concept imaging gives direct evidence of perovskite-based THz sensing in practical applications.

The Vacuolar Molybdate Transporter OsMOT1;2 Controls Molybdenum Remobilization in Rice.

Molybdenum (Mo) is an essential micronutrient for almost all living organisms. The Mo uptake process in plants has been well investigated. However, the mechanisms controlling Mo translocation and remobilization among different plant tissues are largely unknown, especially the allocation of Mo to rice grains that are the major dietary source of Mo for humans. In this study, we characterized the functions of a molybdate transporter, OsMOT1;2, in the interorgan allocation of Mo in rice. Heterologous expression in yeast established the molybdate transport activity of OsMOT1;2. OsMOT1;2 was highly expressed in the blades of the flag leaf and the second leaf during the grain filling stage. Subcellular localization revealed that OsMOT1;2 localizes to the tonoplast. Knockout of OsMOT1;2 led to more Mo accumulation in roots and less Mo translocation to shoots at the seedling stage and to grains at the maturity stage. The remobilization of Mo from older leaves to young leaves under molybdate-depleted condition was also decreased in the osmot1;2 knockout mutant. In contrast, overexpression of OsMOT1;2 enhanced the translocation of Mo from roots to shoots at the seedling stage. The remobilization of Mo from upper leaves to grains was also enhanced in the overexpression lines during grain filling. Our results suggest that OsMOT1;2 may function as a vacuolar molybdate exporter facilitating the efflux of Mo from the vacuole into the cytoplasm, and thus, it plays an important role in the root-to-shoot translocation of Mo and the remobilization of Mo from leaves to grains.

Contrasting resistance of polycyclic aromatic hydrocarbons to atmospheric oxidation influenced by burning conditions.

The oxidation of polycyclic aromatic hydrocarbons (PAHs) determines their lifetime, toxicity and consequent environmental and climate impacts. The residential solid fuel burning composes of a substantial fraction of PAH emissions; however, their oxidation rate is yet to be explicitly understood, which is complicated by the contrasting emission factors under different combustion conditions and their subsequent evolution in the atmosphere. Here we used a plume evolution chamber using ambient oxidants to simulate the evolution of residential solid fuel burning emissions under real-world solar radiation, and then to investigate the oxidation process of the emitted PAHs. Contrasting oxidation rate of PAHs was found to be influenced by particles with or without presence of substantial amount of black carbon (BC). In the flaming burning phase, which contained 46% of BC mass fraction and 8% of organic aerosol (OA) internally mixed with BC, the larger PAHs (with 4-7 rings) was rapidly oxidized 12% for every hour of evolution under solar radiation; however, the larger PAHs from smoldering phase tended to maintain unmodified during the evolution, when 95% of OA was externally mixed with only minor fraction of BC (<5%). This may be ascribed to the complex morphology of BC, allowing more exposure for the internally-mixed OA to the oxidants; in contrast with those externally-mixed OA which was prone to be coated by condensed secondary substances. This raises an important consideration about the particle mixing state in influencing the oxidation of PAHs, particularly the coating on PAHs which may extend their lifetime and environmental impacts.

Molybdenum: More than an essential element.

Molybdenum (Mo) is an essential element for almost all living organisms. After being taken up into the cells as molybdate, it is incorporated into the molybdenum cofactor, which functions as the active site of several molybdenum-requiring enzymes and thus plays crucial roles in multiple biological processes. The uptake and transport of molybdate is mainly mediated by two types of molybdate transporters. The homeostasis of Mo in plant cells is tightly controlled, and such homeostasis likely plays vital roles in plant adaptation to local environments. Recent evidence suggests that Mo is more than an essential element required for plant growth and development; it is also involved in local adaptation to coastal salinity. In this review, we summarize recent research progress on molybdate uptake and transport, molybdenum homeostasis network in plants, and discuss the potential roles of the molybdate transporter in plant adaptation to their local environment.

Diurnal variation and potential sources of indoor formaldehyde at elementary school, high school and university in the Centre Val de Loire region of France.

Formaldehyde (HCHO) is one of the abundant indoor pollutants and has been classified as a human carcinogen by the International Agency for Research on Cancer (IARC). Indoor HCHO at schools is particularly important due to the high occupancy density and the health effects on children. In this study, high time resolved measurement of formaldehyde concentration was conducted in the classrooms at elementary school, high school and university under normal students' activities in three different locations in the Region Centre Val de Loire-France. Indoor average formaldehyde concentrations at those three educational institutions were observed to be in the range 10.96-17.95 µg/m3, not exceeding the World Health Organization (WHO) guideline value of 100 µg/m3. As expected, ventilation was found playing an important role in the control of indoor formaldehyde concentration. After opening windows for 30 min, formaldehyde level decreased by ~25% and 38% in the classroom at the elementary school and the high school, respectively. In addition to the primary sources, the objective of this study was also to determine potential secondary sources of indoor formaldehyde in these schools by measuring the other volatile organic compounds (VOCs) present in the classrooms by a Proton Transfer Reaction Time-of-Flight Mass Spectrometry (PTR-ToF-MS). The measurements suggest that the release of residue from tobacco smokers is one of the major sources of indoor HCHO at the high school, which increases HCHO by ~55% averagely within 1 h. Moreover, the control experiments conducted in the university suggests that VOCs such as that released from cleaning products like terpenes, can contribute to the increase of indoor formaldehyde levels through chemical reactions with ozone. This study confirms simple recommendations to reduce the indoors HCHO concentration in schools: use ventilation systems, limit the emissions like cigarette smoke or cleaning products. It also points out that the secondary sources of formaldehyde must be also considered in the classroom.

Miniaturized Multispectral Detector Derived from Gradient Response Units on Single MAPbX3 Microwire.

Miniaturized multispectral detectors are urgently desired given the unprecedented prosperity of smart optoelectronic chips for integrated functions including communication, imaging, scientific analysis, etc. However, multispectral detectors require complicated prism optics or interference/interferometric filters for spectral recognition, which hampers the miniaturization and their subsequent integration in photonic integrated circuits. In this work, inspired by the advance of computational imaging, optical-component-free miniaturized multispectral detector on 4 mm gradient bandgap MAPbX3 microwire with a diameter of 30 µm, is reported. With accurate composition engineering, halide ions in MAPbX3 microwire vary from Cl to I giving in the gradual variation of optical bandgap from 2.96 to 1.68 eV along axis. The sensing units on MAPbX3 microwire offer the response edge ranging from 450 to 790 nm with the responsivity over 20 mA W-1 , -3dB width over 450 Hz, LDR of ≈60 dB, and a noise current less than ≈1.4 × 10-12 A Hz-0.5 . As a result, the derived miniaturized detector achieves the function of multispectral sensing and discrimination with spectral resolution of ≈25 nm and mismatch of ≈10 nm. Finally, the proof-of-concept colorful imaging is successfully conducted with the miniaturized multispectral detector to further confirm its application in spectral recognition.

P-Type AsP Nanosheet as an Electron Donor for Stable Solar Broad-Spectrum Hydrogen Evolution.

Although research progress on mimicking natural photosynthesis for solar-to-fuel conversion has been continuously made, exploring broadband spectral-responsive materials with suitable band positions and high stability still remains a huge challenge. Herein, we, for the first time, report novel AsP nanosheets (NSs) with P-type semiconducting property and enough negative conduction band, which can work as a stable near-infrared (NIR) region-responsive electron donor for water reductive hydrogen (H2) production. To mimic photosystem I, Au nanorods (NRs) act as electron transport media, which are also responsible for the enhanced electric field nearby, and 1T-MoS2 NSs as a hydrogen evolution catalyst are orderly coupled with AsP NSs with a sheet-rod-sheet structure by electrostatic self-assembly. The cascaded band level alignment enables unidirectional electron flow from AsP to Au and then to MoS2, and the optimum H2 production rate of the MoS2-Au-AsP ternary heterojunction reaches 125.52 µmol g-1 h-1 with good stability even after being stored for several months under light irradiation with a wavelength longer than 700 nm. This work provides a platform that is energetically tailored to drive a solar broad-spectrum fuel generation, including CO2 reduction and N2 fixation.

Microbial diversity formation and maintenance due to temporal niche differentiation caused by low-dose ionizing radiation in oligotrophic environments.

The planetary protection strives to minimize the contamination of microorganisms in spacecrafts. However, it is reported that microbial diversity is abnormally high in the International Space Station (ISS) after long-term exposure to low-dose ionizing radiation (LDIR). It remains a mystery why LDIR leads to the formation and maintenance of high microbial diversity in oligotrophic environments like the ISS. In this study, an artificial microbial community has been cultivated without and with LDIR, respectively. The microbial community was composed of three common microbial species, i.e., Bacillus subtilis, Escherichia coli and Pseudomonas aeruginosa in the ISS. After analyzing the differences in microbial physiological and behavioral response characteristics in the two scenarios, a reasonable hypothesis was proposed to elucidate the formation and maintenance mechanisms of high microbial diversity in oligotrophic environments with the LDIR. Then a set of kinetic models with time-lag were developed based on this hypothesis, observed phenomena, and experimental data. Finally, these kinetic models were sufficiently validated, and the hypothesis was fully confirmed through large-scale digital simulations. Briefly, as a decisive succession mechanism in oligotrophic environments with LDIR, temporal niche differentiation (TND) caused by microbial delayed responses to LDIR can give rise to asynchronously convergent fluctuations of microbial populations and significantly alleviate the intra- and interspecific competitions. Such a mechanism can drive the microbial communities in oligotrophic environments with LDIR to form and maintain high species diversity.

Ultrasound Image Features under Deep Learning in Breast Conservation Surgery for Breast Cancer.

This study was to analyze the effect of the combined application of deep learning technology and ultrasound imaging on the effect of breast-conserving surgery for breast cancer. A deep label distribution learning (LDL) model was designed, and the semiautomatic segmentation algorithm based on the region growing and active contour technology (RA) and the segmentation model based on optimized nearest neighbors (ON) were introduced for comparison. The designed algorithm was applied to the breast-conserving surgery of breast cancer patients. According to the difference in intraoperative guidance methods, 102 female patients with early breast cancer were divided into three groups: 34 cases in W1 group (ultrasound guidance based on deep learning segmentation model), 34 cases in W2 group (ultrasound guidance), and 34 cases in W3 group (palpation guidance). The results revealed that the tumor area segmented by the LDL algorithm constructed in this study was closer to the real tumor area; the segmentation accuracy (AC), Jaccard, and true-positive (TP) values of the LDL algorithm were obviously greater than those of the RA and ON algorithms, while the false-positive (FP) value was significantly lower in contrast to the RA and ON algorithms, showing statistically observable differences (P < 0.05); the actual resection volume of the patients in the W1 group was the closest to the ideal resection volume, which was much smaller in contrast to that of the patients in the W2 and W3 groups, showing statistical differences (P < 0.05); the positive margins of the patients in the W1 group were statistically lower than those in the W2 and W3 groups (P < 0.05). In addition, 1 patient in the W1 group was not satisfied with the cosmetic effect, 3 patients in the W2 group were not satisfied with the cosmetic effect, and 9 patients in the W3 group were not satisfied with the cosmetic effect. Finally, it was found that the ultrasound image based on the deep LDL model effectively improved the AC of tumor resection and negative margins, reduced the probability of normal tissue being removed, and improved the postoperative cosmetic effect of breast.

MicroRNA-1298-5p inhibits the tumorigenesis of breast cancer by targeting E2F1.

Studies performed in the last two decades have identified microRNA (miR)-1298-5p to display tumor-suppressive functions in several types of malignancy. In addition, the regulatory role of E2F transcription factor 1 (E2F1) has been reported in multiple types of cancer, including breast cancer (BC). However, whether miR-1298-5p participates in BC progression and whether a regulatory association exists between miR-1298-5p and E2F1 remains to be explored. The present study aimed to determine the role of miR-1298-5p and its interaction with E2F1 in BC. The expression of miR-1298-5p and E2F1 was examined by reverse transcription-quantitative PCR and western blot assays. The viability and proliferative capacity of BC cells were evaluated by Cell Counting Kit-8 and 5-bromo-2'-deoxyuridine assays, respectively. The apoptotic rate was assessed by the caspase-3 activity assay and flow cytometry; the protein expression levels of vimentin and E-cadherin were evaluated by western blotting. In addition, the adhesive and migratory abilities of BC cells were determined by conducting cell adhesion and wound healing assay, respectively. The target relationship between miR-1298-5p and E2F1 was validated by the luciferase reporter assay. The results of the present study revealed that the levels of miR-1298-5p were downregulated in BC tissues and cells compared with those in normal breast tissues and cells, respectively. In addition, miR-1298-5p was demonstrated to inhibit the proliferation, adhesion and migration of BC cells and to promote BC cell apoptosis. E2F1 was verified as a target gene of miR-1298-5p using the luciferase reporter assay. Additionally, E2F1 exhibited an opposite expression pattern compared with that of miR-1298-5p in BC tissues. Furthermore, the downregulation of miR-1298-5p in BC cells was reversed by silencing E2F1. Overall, the results of the present study suggested that miR-1298-5p repressed BC cell proliferation, adhesion and migration, and enhanced BC cell apoptosis by downregulating E2F1.