Light modulates glucose metabolism by a retina-hypothalamus-brown adipose tissue axis.

Public health studies indicate that artificial light is a high-risk factor for metabolic disorders. However, the neural mechanism underlying metabolic modulation by light remains elusive. Here, we found that light can acutely decrease glucose tolerance (GT) in mice by activation of intrinsically photosensitive retinal ganglion cells (ipRGCs) innervating the hypothalamic supraoptic nucleus (SON). Vasopressin neurons in the SON project to the paraventricular nucleus, then to the GABAergic neurons in the solitary tract nucleus, and eventually to brown adipose tissue (BAT). Light activation of this neural circuit directly blocks adaptive thermogenesis in BAT, thereby decreasing GT. In humans, light also modulates GT at the temperature where BAT is active. Thus, our work unveils a retina-SON-BAT axis that mediates the effect of light on glucose metabolism, which may explain the connection between artificial light and metabolic dysregulation, suggesting a potential prevention and treatment strategy for managing glucose metabolic disorders.

Melanopsin retinal ganglion cells mediate light-promoted brain development.

During development, melanopsin-expressing intrinsically photosensitive retinal ganglion cells (ipRGCs) become light sensitive much earlier than rods and cones. IpRGCs project to many subcortical areas, whereas physiological functions of these projections are yet to be fully elucidated. Here, we found that ipRGC-mediated light sensation promotes synaptogenesis of pyramidal neurons in various cortices and the hippocampus. This phenomenon depends on activation of ipRGCs and is mediated by the release of oxytocin from the supraoptic nucleus (SON) and the paraventricular nucleus (PVN) into cerebral-spinal fluid. We further characterized a direct connection between ipRGCs and oxytocin neurons in the SON and mutual projections between oxytocin neurons in the SON and PVN. Moreover, we showed that the lack of ipRGC-mediated, light-promoted early cortical synaptogenesis compromised learning ability in adult mice. Our results highlight the importance of light sensation early in life on the development of learning ability and therefore call attention to suitable light environment for infant care.

Heterothermic Cataluminescence Sensor System for Efficient Determination of Aldehyde Molecules.

A simple and stable cataluminescence (CTL) sensing platform based on a single sensing material for effective and rapid detection of aldehydes is an urgent need due to growing concerns for the environment, security, and health. Here, an effective and user-friendly identification method is successfully proposed to determine six common aldehydes of homologous compounds via a heterothermic CTL sensor system. Using Gd2O3 with excellent catalytic activity as a sensing material, thermodynamic and kinetic insights into the interactions between Gd2O3 and aldehydes at different temperatures were extracted and integrated to generate a unique constellation profile for each tested aldehyde, whereby achieving their effective and prompt determination. Moreover, the sensor system allowed the quantitative analysis of aldehydes with detection limits of 0.001, 0.009, 0.011, 0.011, 0.007, and 0.003 µg mL-1. Significantly, the sensor system had an excellent stability of up to 30 days. The CTL sensing platform was constructed based on a thermal regulation strategy that can provide a new approach to chemical agent identification.

High-Coupled Magnetic-Levitation Hybrid Nanogenerator with Frequency Multiplication Effect for Wireless Water Level Alarm.

Hybrid nanogenerators (HNGs) represent a promising avenue for water energy harvesting, yet their commercial viability faces hurdles such as limited power output, poor coupling, and constrained operational lifespans. Here, a highly coupled triboelectric-electromagnetic magnetic-levitation hybrid nanogenerator (ML-HNG) is introduced that shows great potential for water energy harvesting. The ML-HNG fulfills the challenges of high power output, strong coupling, and long operational lifespans. During the contact-separation process of the triboelectric nanogenerator (TENG), the changing magnetic flux in the electromagnetic generator's coils generates a potential difference between the coils and Cu electrodes. The unique design of the ML-HNG employs a shared coil electrode configuration, which enhances the coupling without adding extra volume. This integration allows the ML-HNG to achieve multi-frequency vibrations and multiple output cycles per external longitudinal movement, a phenomenon known as the frequency multiplication effect. With an average power density of 1.69 W m-3 in water, the ML-HNG provides continuous power for a thermo-hygrometer and can quickly drive a wireless water level alarm system within a minute. This groundbreaking hybrid nanogenerator design holds significant promise for the efficient and consistent harvesting of low-frequency ocean wave energy, marking a substantial advancement in blue energy technology.

Elastic Self-Recovering Hybrid Nanogenerator for Water Wave Energy Harvesting and Marine Environmental Monitoring.

To achieve large-scale development of triboelectric nanogenerators (TENGs) for water wave energy harvesting and powering the colossal sensors widely distributed in the ocean, facile and scalable TENGs with high output are urgently required. Here, an elastic self-recovering hybrid nanogenerator (ES-HNG) is proposed for water wave energy harvesting and marine environmental monitoring. The elastic skeletal support of the ES-HNG is manufactured using three-dimensional (3D) printing technology, which is more conducive to the large-scale integration of the ES-HNG. Moreover, the combination of a TENG and an electromagnetic generator (EMG) optimizes the utilization of device space, leading to enhanced energy harvesting efficiency. Experimental results demonstrate that the TENG achieves a peak power output of 42.68 mW, and the EMG reaches a peak power output of 4.40 mW. Furthermore, various marine environment monitoring sensors, such as a self-powered wireless meteorological monitoring system, a wireless alarm system, and a water quality monitoring pen, have been successfully powered by the sophisticated ES-HNG. This work introduces an ES-HNG for water wave energy harvesting, which demonstrates potential in marine environment monitoring and offers a new solution for the sustainable development of the marine internet of things.

Instant Fingerprint Discrimination for Military Explosive Vapors by Dy3+ Doping a La2O3-Based Cataluminescence Sensor System.

With the intensification of explosive-based terrorism attack and environmental concerns, the innovation of high-efficiency and portable sensors for facile, rapid, and reliable monitoring of explosives has become one of the major demands in societies. Herein, a reliable and easy-to-use cataluminescence sensor system based on Dy3+ doping La2O3 nanorod catalysts has been developed for the identification and detection of six types of military explosive vapors, including homologous compounds and even isomers. The efficient discrimination is to make full use of the thermodynamic and kinetic information that can be extracted from the catalytic oxidation process of explosive molecules on various sensing materials, that is, the response signal and response time to generate the fingerprint of each target compound, while the rapid detection of the strategy can be manifested in response toward six military explosive vapors within 2.5 s and recover within 4 s. Meanwhile, the quantitative analysis of the explosives by the sensor system was realized based on 0.8%Dy:La2O3 with optimal catalytic activity, and the detection limits of NB, m-MNT, m-DNB, PNT, DNT, and TNT can reach 0.62, 0.49, 0.63, 0.38, 0.023, and 0.067 µg mL-1. In this research, we also constructed a novel sensor device and detection platform for explosive monitoring, which is of great significance for providing a new sensing principle for the efficient identification of explosives.

Efficient Photoinduced Thermocatalytic Chemiluminescence System Based on the Z-Scheme Heterojunction Ag3PO4/Ag/Bi4Ti3O12 for H2S Sensing.

Cataluminescence as a highly efficient gas transduction principle has attracted wide attention among research in environmental monitoring and clinical diagnosis with increasing awareness of human safety. Nowadays, the development of innovation sensing systems and the construction of the sensing mechanism to improve the analytical performance of compounds remain a major challenge. Herein, we construct an advanced photoinduced thermocatalytic chemiluminescence (PI-TC-CL) gas-sensing system via the introduction of a Z-scheme heterojunction Ag3PO4/Ag/Bi4Ti3O12 to achieve higher efficient detection of H2S. The unique electron transport path of the Z-scheme heterojunction and the LSPR effect of Ag nanoparticles fascinate the generation of the photoinduced electron-hole pair on the surface of catalysts when stimulated by LED lamps and slow down the recombination of electron-hole pairs under thermal conditions. Thus, based on the cooperative effect of the Z-scheme heterojunction AgPO/Ag/BTO and PI-TC-CL system, we have successfully established an efficient H2S CTL detection system, which has a response three times higher than that on the traditional CTL system and even 45 times higher than that on BTO and ranges among the best of the state-of-the-art CTL performance in H2S detection with the linear range of 0.095-8.87 µg mL-1 and a limit of detection of 0.0065 µg mL-1. Besides, to explore the gas-sensing mechanism, the synergetic effects of photoinduction and thermal catalysis are investigated thoroughly via conductivity and electrochemical experiments. This research provides a new perspective of engineering highly efficient catalysts and ingenious sensor systems through designing the nanostructure of materials and synergism catalytic mechanism.

Cataluminescence System Coupled with Vacuum Desorption-Sampling Methodology for Real-Time Ozone Sensing during the Self-Decomposition Process on Functional Boron Nitride.

The treatment and detection of ozone have been widely studied in recent decades with respect to toxicity and contamination, while the measurement method of ozone is relatively toneless. Fortunately, a new concept of the cataluminescence (CTL) sensor provides a scheme of real-time ozone sensing in a tiny system. Here, a novel CTL sensor system was specially developed with silica-hydroxyl functional boron nitride as the sensing material for rapid and sensitive ozone detection. Coupled with the construction of a pulse vacuum static sampling system, ozone on the surface of sensing material can be desorbed rapidly and can step into the next detection circulation in a few seconds. Based on the strong emission initiated by the transient of reactive oxygen species (ROS) including singlet oxygen, a trioxide group, and an oxygen radical, the detection limit of ozone could be optimized to be as low as 51.2 ppb. Besides, the sensor system exhibited remarkable anti-interference performance in which humidity changes and common VOCs do not disturb or weakly disturb ozone sensing, and the CTL mechanism of the multistep degradation process was further discussed on the basis of multiple pieces of experimental evidence and a DFT transient calculation. A real-time degradation-sensing module was further attached to the system to realize the functions of ozone decomposition and real-time monitoring.

An encoder-decoder network for direct image reconstruction on sinograms of a long axial field of view PET.

PURPOSE: Deep learning is an emerging reconstruction method for positron emission tomography (PET), which can tackle complex PET corrections in an integrated procedure. This paper optimizes the direct PET reconstruction from sinogram on a long axial field of view (LAFOV) PET. METHODS: This paper proposes a novel deep learning architecture to reduce the biases during direct reconstruction from sinograms to images. This architecture is based on an encoder-decoder network, where the perceptual loss is used with pre-trained convolutional layers. It is trained and tested on data of 80 patients acquired from recent Siemens Biograph Vision Quadra long axial FOV (LAFOV) PET/CT. The patients are randomly split into a training dataset of 60 patients, a validation dataset of 10 patients, and a test dataset of 10 patients. The 3D sinograms are converted into 2D sinogram slices and used as input to the network. In addition, the vendor reconstructed images are considered as ground truths. Finally, the proposed method is compared with DeepPET, a benchmark deep learning method for PET reconstruction. RESULTS: Compared with DeepPET, the proposed network significantly reduces the root-mean-squared error (NRMSE) from 0.63 to 0.6 (p < 0.01) and increases the structural similarity index (SSIM) and peak signal-to-noise ratio (PSNR) from 0.93 to 0.95 (p < 0.01) and from 82.02 to 82.36 (p < 0.01), respectively. The reconstruction time is approximately 10 s per patient, which is shortened by 23 times compared with the conventional method. The errors of mean standardized uptake values (SUVmean) for lesions between ground truth and the predicted result are reduced from 33.5 to 18.7% (p = 0.03). In addition, the error of max SUV is reduced from 32.7 to 21.8% (p = 0.02). CONCLUSION: The results demonstrate the feasibility of using deep learning to reconstruct images with acceptable image quality and short reconstruction time. It is shown that the proposed method can improve the quality of deep learning-based reconstructed images without additional CT images for attenuation and scattering corrections. This study demonstrated the feasibility of deep learning to rapidly reconstruct images without additional CT images for complex corrections from actual clinical measurements on LAFOV PET. Despite improving the current development, AI-based reconstruction does not work appropriately for untrained scenarios due to limited extrapolation capability and cannot completely replace conventional reconstruction currently.

Evaluating the Band Gaps of Semiconductors by Cataluminescence.

A rapid and efficient methodology for the evaluation of band gaps of semiconductors is highly desirable to analyze and assess the intrinsic properties and extending application scopes of semiconductor materials. Here, the negative correlation of the cataluminescence (CTL) signal in the presence of H2S and the band gap of Aurivillius-type perovskite oxide Bi4+nFenTi3O12+3n (n = 1-4) was confirmed, where the H2S-induced CTL signal acts as a probe to evaluate the band gaps of semiconductor materials. The related mechanism shows that the thermal energy obtained by heating makes the electrons in the valence band more easily excite into the conduction band of a narrower band gap material and further promotes electron transfer between the gaseous compounds and semiconductor materials, causing acceleration of the catalytic oxide process. In addition, the extensibility was further verified by exploring the layered perovskite containing other insertion structures, including Bi4+nConTi3O12+3n (n = 1-4), Bi5NiTi3O15, and Bi5MnTi3O15, which was also consistent with the results characterized by UV diffuse reflectance spectroscopy. The established CTL probe for band gap evaluation shows rapid response, is simple to operate, and is of low cost, which is expected to become an innovative alternative to the conventional band gap assessment approach.

Ratiometric Cataluminescence Sensor of Amine Vapors for Discriminating Meat Spoilage.

The freshness of meat has always been the focus of attention from consumers and suppliers for health and economic reasons. Usually, amine vapors, as one of the main components of the gas produced in the process of meat spoilage, can be used to monitor meat spoilage. Here, a new ratiometric cataluminescence (CTL) sensor based on energy transfer was developed to identify amine vapors and monitor meat freshness. After Tb doping, amine vapors exhibit a dual-wavelength (490 and 555 nm) property of CTL signals when reacted on the surface of Tb-doped La2O2CO3, and the ratio of I555 to I490 (R555/490) is a unique value for a given analyte within a wide range of concentrations. To illustrate the new sensor, 15 amine vapors were successfully identified using R555/490, including homologues and isomers. Besides, this sensor was used to monitor four meats, and the freshness of meats can be distinguished by cluster analysis successfully. Moreover, further discussion of energy-transfer phenomena and influence factors has facilitating effects on exploring the mechanism of energy transfer at the gas-solid interface.

Tomoelastography Based on Multifrequency MR Elastography for Prostate Cancer Detection: Comparison with Multiparametric MRI.

Background Multiparametric MRI is used for depiction of prostate cancer (PCa) but without consideration of the mechanical alteration of prostatic tissue by cancer. Purpose To investigate the diagnostic performance of stiffness and fluidity quantified with tomoelastography, a multifrequency MR elastography technique, for depiction of PCa compared with multiparametric MRI with Prostate Imaging Reporting and Data System (PI-RADS) version 2.1. Materials and Methods Prospective participants suspected to have PCa and healthy controls (HCs) underwent multiparametric MRI and tomoelastography between March 2019 and July 2020. Tomoelastography maps of shear-wave speed (c) and loss angle (φ) quantified stiffness and fluidity, respectively, for PCa and benign prostatic disease and for the peripheral and transition zones in HCs. Differences between entities and regions were analyzed by using analysis of variance or Kruskal-Wallis test. Diagnostic performance was assessed with area under the receiver operating characteristic curve (AUC) analysis. Results There were 73 participants with PCa (mean age, 72 years ± 7 [standard deviation]), 82 with benign prostatic disease (66 years ± 7), and 53 HCs (41 years ± 14). Mean ± standard deviation of c and φ were higher in PCa (3.4 m/sec ± 0.6 and 1.3 radian ± 0.2, respectively) than in benign prostatic disease (2.6 m/sec ± 0.3 and 1.0 radian ± 0.2, respectively; P < .001) and age-matched HCs (2.2 m/sec ± 0.1 and 0.8 radian ± 0.1, respectively; P < .001). Incorporating c and φ (AUC, 0.95; 95% CI: 0.92, 0.98) improved the diagnostic performance of PI-RADS version 2.1 (AUC, 0.85; 95% CI: 0.80, 0.91; P < .001). Multiparametric MRI combined with c and φ enabled detection of PCa with 95% (78 of 82 non-PCa) specificity, which was significantly higher than with use of multiparametric MRI alone (77% [63 of 82 non-PCa]; P < .001). In regional analysis, c combined with φ enabled differentiation of transition zone PCa from benign prostatic hyperplasia (AUC, 0.91; 95% CI: 0.83, 0.98) and peripheral zone PCa from chronic prostatitis (AUC, 0.94; 95% CI: 0.88, 1.00). Conclusion Use of tomoelastography-quantified stiffness and fluidity improved the diagnostic performance of multiparametric MRI with Prostate Imaging Reporting and Data System version 2.1 in detecting cancer in both the peripheral and transition zones. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Hectors and Lewis in this issue. An earlier incorrect version of this article appeared online. This article was corrected on March 24, 2021.

Abdominal perivascular epithelioid cell tumor (PEComa) without visible fat: a clinicopathologic and radiological analysis of 16 cases.

OBJECTIVE: To retrospectively review the clinicopathological features and computed tomography (CT) and magnetic resonance imaging (MRI) findings of abdominal perivascular epithelioid cell tumor without visible fat (PEComawvf). MATERIALS AND METHODS: Sixteen patients with surgically and pathologically confirmed perivascular epithelioid cell tumor without visible fat were enrolled. Their clinicopathological data and imaging findings were retrospectively reviewed. The CT and MRI features, including location, size, shape, margin, density, calcification, cystic necrosis and enhancement pattern, were analyzed. RESULTS: There were 4 males and 12 females (median age, 46 years; range, 21-65 years) in this study. All 16 patients were diagnostic asymptomatic unenhanced CT or MRI and revealed a well-defined (n = 13), oval (n = 10), mass with heterogeneous (n = 6) or homogeneous density/signal intensity (n = 7), calcification and hemorrhage was no found in any cases. On enhanced CT/MRI, markedly enhancement patterns (n = 14) were observed. The "peripheral enhancement" sign was observed in 13 cases. One in 16 cases recurrence was discovered during the follow-up period. CONCLUSIONS: Dynamic CT, MRI and pathology of PEComawvf had some characteristics of non-aggressive pattern of performance, and MRI would provide beneficial detection of microscopic fat. Enhanced imaging showed PEComawvf is characterized by a "peripheral enhancement" with a marked enhancement pattern. Knowing these characteristics could contribute to improving the understanding abdominal PEComawvf and related palliative care.

Recent advances in methodologies and applications of cataluminescence sensing.

Cataluminescence (CTL), a kind of chemiluminescence emitted at the gas-solid interface during catalytic oxidation reactions, has been developed for many decades as a novel and promising gas sensing technique. In this review, we introduce the origin, basic principles, and mechanisms of CTL sensing systems and summarize the recent advances in CTL sensing, focusing on methodologies and extended applications such as in gas selective monitoring, recognition of complex mixture, evaluation for catalytic property and use in high-performance liquid chromatography, capillary electrophoresis and gas chromatography detectors. In addition, development prospects and some challenges facing CTL-based sensing are also discussed.

Ratiometric Cataluminescence for Rapid Recognition of Volatile Organic Compounds Based on Energy Transfer Process.

Recognition of volatile organic compounds (VOCs) is a hot topic full of challenge from the perspective of environmental protection and human security. Here, we developed a novel ratiometric cataluminescence (RCTL) method for fast identification and detection gas compounds at various concentrations based on the energy transfer process, by the means of introducing rare earth ions codoped metal oxide into cataluminescence (CTL) sensor system to work as sensing material. When the prepared stick-like Y2O3:Eu3+,Tb3+ is exposed to kinds of analytes, different energy transfer process take place to emit two new signals at the characteristic wavelength of Tb3+ (ITb) and Eu3+ (IEu), which is available for us to identify miscellaneous gaseous compounds rely on the ratio of ITb to IEu (ITb/IEu). To confirm the feasibility of the proposed method, seven kinds of gas compounds, including homologous series and even structural isomers, were investigated and successfully distinguished in a wide range of concentrations. Besides, further discussion of the CTL sensing and recognition mechanism in this paper has facilitating effects on exploring reactive intermediates and explaining the essential principle of catalytic oxidation process.

Persistent sulfate formation from London Fog to Chinese haze.

Sulfate aerosols exert profound impacts on human and ecosystem health, weather, and climate, but their formation mechanism remains uncertain. Atmospheric models consistently underpredict sulfate levels under diverse environmental conditions. From atmospheric measurements in two Chinese megacities and complementary laboratory experiments, we show that the aqueous oxidation of SO2 by NO2 is key to efficient sulfate formation but is only feasible under two atmospheric conditions: on fine aerosols with high relative humidity and NH3 neutralization or under cloud conditions. Under polluted environments, this SO2 oxidation process leads to large sulfate production rates and promotes formation of nitrate and organic matter on aqueous particles, exacerbating severe haze development. Effective haze mitigation is achievable by intervening in the sulfate formation process with enforced NH3 and NO2 control measures. In addition to explaining the polluted episodes currently occurring in China and during the 1952 London Fog, this sulfate production mechanism is widespread, and our results suggest a way to tackle this growing problem in China and much of the developing world.

Emerging roles and regulation of MiT/TFE transcriptional factors.

The MiT/TFE transcription factors play a pivotal role in the regulation of autophagy and lysosomal biogenesis. The subcellular localization and activity of MiT/TFE proteins are primarily regulated through phosphorylation. And the phosphorylated protein is retained in the cytoplasm and subsequently translocates to the nucleus upon dephosphorylation, where it stimulates the expression of hundreds of genes, leading to lysosomal biogenesis and autophagy induction. The transcription factor-mediated lysosome-to-nucleus signaling can be directly controlled by several signaling molecules involved in the mTORC1, PKC, and AKT pathways. MiT/TFE family members have attracted much attention owing to their intracellular clearance of pathogenic factors in numerous diseases. Recently, multiple studies have also revealed the MiT/TFE proteins as master regulators of cellular metabolic reprogramming, converging on autophagic and lysosomal function and playing a critical role in cancer, suggesting that novel therapeutic strategies could be based on the modulation of MiT/TFE family member activity. Here, we present an overview of the latest research on MiT/TFE transcriptional factors and their potential mechanisms in cancer.

Assessing the effects of anthropogenic aerosols on Pacific storm track using a multiscale global climate model.

Atmospheric aerosols affect weather and global general circulation by modifying cloud and precipitation processes, but the magnitude of cloud adjustment by aerosols remains poorly quantified and represents the largest uncertainty in estimated forcing of climate change. Here we assess the effects of anthropogenic aerosols on the Pacific storm track, using a multiscale global aerosol-climate model (GCM). Simulations of two aerosol scenarios corresponding to the present day and preindustrial conditions reveal long-range transport of anthropogenic aerosols across the north Pacific and large resulting changes in the aerosol optical depth, cloud droplet number concentration, and cloud and ice water paths. Shortwave and longwave cloud radiative forcing at the top of atmosphere are changed by -2.5 and +1.3 W m(-2), respectively, by emission changes from preindustrial to present day, and an increased cloud top height indicates invigorated midlatitude cyclones. The overall increased precipitation and poleward heat transport reflect intensification of the Pacific storm track by anthropogenic aerosols. Hence, this work provides, for the first time to the authors' knowledge, a global perspective of the effects of Asian pollution outflows from GCMs. Furthermore, our results suggest that the multiscale modeling framework is essential in producing the aerosol invigoration effect of deep convective clouds on a global scale.

Influence of physical education on anxiety, depression, and self-esteem among college students.

BACKGROUND: Physical education is pivotal in our country's education reform. Urban schools have notably enhanced the intensity of physical education in recent years. However, the effects of physical education on students' anxiety, depression, and self-esteem levels, as well as their interrelations, remain unexplored. AIM: To analyze the influence of physical education on students' anxiety, depression, and self-esteem. METHODS: This study employed a cross-sectional design. A stratified cluster sampling method was used to select 478 first-year university students. Self-administered questionnaires were used to investigate the physical education status and basic information of college students. We used the Physical Activity Rank Scale-3 (PARS-3), Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), and Self-Esteem Scale (SES) to assess the level of exercise, anxiety, depression, and self-esteem. Multiple Logistic regression was used to analyze the factors influencing anxiety, depression, and low self-esteem. The receiver operating characteristic curve and area under the curve (AUC) were used to evaluate the predictive ability of PARS-3 scores for anxiety, depression, and low self-esteem. Spearman's correlation was used to analyze the correlations among the PARS-3, SAS, SDS, and SES. RESULTS: Compared with the domestic norms, SAS and SDS scores were higher, and SES scores were lower (P < 0.05). Among the participants, 210 (43.93%) had PARS-3 scores below 20, 94 (19.67%) had scores of 20-42, and 174 (36.40%) had scores above 42. After adjusting for daily sleep time, gender, being an only child, major, father's educational background, mother's educational background, and family residence, PARS-3 scores were independent influencing factors for anxiety, depression, and low self-esteem (P < 0.05). The AUC of PARS-3 scores predicting anxiety, depression, and low self-esteem were 0.805 (0.760-0.849), 0.799 (0.755-0.843), and 0.831 (0.788-0.874), respectively. The sensitivities were 0.799, 0.801, and 0.748, and the specificities were 0.743, 0.716, and 0.814, respectively. PARS-3 was negatively correlated with SAS and SDS scores (r = -0.566, -0.621, both P < 0.001) and positively correlated with SES scores (r = -0.621, P < 0.001). SES scores were negatively correlated with SAS and SDS scores (r = -0.508, r = -0.518, both P < 0.001). CONCLUSION: The amount of physical activity is negatively correlated with anxiety and depression degree and positively correlated with self-esteem degree.