[Vertical Distribution Characteristics and Driving Factors of Bacterioplankton and Nitrogen Phosphorus Cycle Genes in Danjiangkou Reservoir].

Danjiangkou Reservoir is a critical water source for the South-to-North Water Diversion Project, which harbors a diverse bacterioplankton community with varying depths, and the understanding of its nitrogen and phosphorus cycle and associated driving factors remains limited. In this study, we selected five ecological sites within Danjiangkou Reservoir and conducted metagenomics analysis to investigate the vertical distribution of bacterioplankton communities in the surface, middle, and bottom layers. Furthermore, we analyzed and predicted the function of nitrogen and phosphorus cycles, along with their driving factors. Our findings revealed the dominance of Proteobacteria, Actinobacteria, and Planctomycetes in the Danjiangkou Reservoir. Significant differences were observed in the structure of bacterioplankton communities across different depths, with temperature （T）, oxidation-reduction potential （ORP）, dissolved oxygen （DO）, and Chla identified as primary factors influencing the bacterioplankton composition. Analysis of nitrogen cycle functional genes identified 39 genes, including gltB, glnA, gltD, gdhA, NRT, etc., which were involved in seven main pathways, encompassing nitrogen fixation, nitrification, denitrification, and dissimilatory nitrate reduction. Phosphorus cycle function gene analysis identified 54 genes, including pstS, ppx-gppA, glpQ, ppk1, etc., primarily participating in six main pathways, including organic P mineralization, inorganic P solubilization, and regulatory. Cluster analysis indicated that different depths were significant factors influencing the composition and abundance of nitrogen and phosphorus cycle functional genes. The composition and abundance of nitrogen and phosphorus cycle functional genes in the surface and bottom layers differed and were generally higher than those in the middle layer. Deinococcus, Hydrogenophaga, Limnohabitans, Clavibacter, and others were identified as key species involved in the nitrogen and phosphorus cycle. Additionally, we found significant correlations between nitrogen and phosphorus cycle functional genes and environmental factors such as DO, pH, T, total dissolved solids （TDS）, electrical conductivity （EC）, and Chla. Furthermore, the content of these environmental factors exhibited depth-related changes in the Danjiangkou Reservoir, resulting in a distinct vertical distribution pattern of bacterioplankton nitrogen and phosphorus cycle functional genes. Overall, this study sheds light on the composition, function, and influencing factors of bacterioplankton communities across different layers of Danjiangkou Reservoir, offering valuable insights for the ecological function and diversity protection of bacterioplankton in this crucial reservoir ecosystem.

Equol: a metabolite of gut microbiota with potential antitumor effects.

An increasing number of studies have shown that the consumption of soybeans and soybeans products is beneficial to human health, and the biological activity of soy products may be attributed to the presence of Soy Isoflavones (SI) in soybeans. In the intestinal tracts of humans and animals, certain specific bacteria can metabolize soy isoflavones into equol. Equol has a similar chemical structure to endogenous estradiol in the human body, which can bind with estrogen receptors and exert weak estrogen effects. Therefore, equol plays an important role in the occurrence and development of a variety of hormone-dependent malignancies such as breast cancer and prostate cancer. Despite the numerous health benefits of equol for humans, only 30-50% of the population can metabolize soy isoflavones into equol, with individual variation in gut microbiota being the main reason. This article provides an overview of the relevant gut microbiota involved in the synthesis of equol and its anti-tumor effects in various types of cancer. It also summarizes the molecular mechanisms underlying its anti-tumor properties, aiming to provide a more reliable theoretical basis for the rational utilization of equol in the field of cancer treatment.

The gut microbiota derived metabolite trimethylamine N-oxide: Its important role in cancer and other diseases.

An expanding body of research indicates a correlation between the gut microbiota and various diseases. Metabolites produced by the gut microbiota act as mediators between the gut microbiota and the host, interacting with multiple systems in the human body to regulate physiological or pathological functions. However, further investigation is still required to elucidate the underlying mechanisms. One such metabolite involved in choline metabolism by gut microbes is trimethylamine (TMA), which can traverse the intestinal epithelial barrier and enter the bloodstream, ultimately reaching the liver where it undergoes oxidation catalyzed by flavin-containing monooxygenase 3 (FMO3) to form trimethylamine N-oxide (TMAO). While some TMAO is eliminated through renal excretion, remaining amounts circulate in the bloodstream, leading to systemic inflammation, endoplasmic reticulum (ER) stress, mitochondrial stress, and disruption of normal physiological functions in humans. As a representative microbial metabolite originating from the gut, TMAO has significant potential both as a biomarker for monitoring disease occurrence and progression and for tailoring personalized treatment strategies for patients. This review provides an extensive overview of TMAO sources and its metabolism in human blood, as well as its impact on several major human diseases. Additionally, we explore the latest research areas related to TMAO along with future directions.

Plant Growth-Promoting Bacteria Influence Microbial Community Composition and Metabolic Function to Enhance the Efficiency of Hybrid pennisetum Remediation in Cadmium-Contaminated Soil.

The green and efficient remediation of soil cadmium (Cd) is an urgent task, and plant-microbial joint remediation has become a research hotspot due to its advantages. High-throughput sequencing and metabolomics have technical advantages in analyzing the microbiological mechanism of plant growth-promoting bacteria in improving phytoremediation of soil heavy metal pollution. In this experiment, a pot trial was conducted to investigate the effects of inoculating the plant growth-promoting bacterium Enterobacter sp. VY on the growth and Cd remediation efficiency of the energy plant Hybrid pennisetum. The test strain VY-1 was analyzed using high-throughput sequencing and metabolomics to assess its effects on microbial community composition and metabolic function. The results demonstrated that Enterobacter sp. VY-1 effectively mitigated Cd stress on Hybrid pennisetum, resulting in increased plant biomass, Cd accumulation, and translocation factor, thereby enhancing phytoremediation efficiency. Analysis of soil physical-chemical properties revealed that strain VY-1 could increase soil total nitrogen, total phosphorus, available phosphorus, and available potassium content. Principal coordinate analysis (PCoA) indicated that strain VY-1 significantly influenced bacterial community composition, with Proteobacteria, Firmicutes, Chloroflexi, among others, being the main differential taxa. Redundancy analysis (RDA) revealed that available phosphorus, available potassium, and pH were the primary factors affecting bacterial communities. Partial Least Squares Discriminant Analysis (PLS-DA) demonstrated that strain VY-1 modulated the metabolite profile of Hybrid pennisetum rhizosphere soil, with 27 differential metabolites showing significant differences, including 19 up-regulated and eight down-regulated expressions. These differentially expressed metabolites were primarily involved in metabolism and environmental information processing, encompassing pathways such as glutamine and glutamate metabolism, α-linolenic acid metabolism, pyrimidine metabolism, and purine metabolism. This study utilized 16S rRNA high-throughput sequencing and metabolomics technology to investigate the impact of the plant growth-promoting bacterium Enterobacter sp. VY-1 on the growth and Cd enrichment of Hybrid pennisetum, providing insights into the regulatory role of plant growth-promoting bacteria in microbial community structure and metabolic function, thereby improving the microbiological mechanisms of phytoremediation.

Phosphorus depletion is exacerbated by increasing nitrogen loading in the Bohai sea.

Phosphorus (P) is an essential nutrient for algal growth in nearshore ecosystems. In recent years, there has been a shift in nutrient dynamics in nearshore areas, leading to an exacerbation of P limitation, although the underlying mechanisms remain unclear. This study analyzed the P species and budget in the Bohai Sea (BS) from 2011 to 2020, aiming to explore the intrinsic mechanisms of P limitation in the BS. The results show that the main external source of P in the BS was river transport (89%), and the primary fate of P was burial (96%) into the sediment. Due to excessive nitrogen (N) input and biological processes in the BS, the P budget in the BS is unbalanced, resulting in an increase in the N/P ratio, particularly in nearshore areas. Nearshore areas typically have lower concentrations of dissolved inorganic P (DIP) in the water and higher concentrations of reactive P (Reac-P) in the sediments. This pattern is particularly evident in Bohai Bay and the northwest nearshore region, where harmful algal blooms occur frequently. To cope with enhanced P limitation, the biologically driven P regeneration and cycling processes within the BS are accelerated. From 2011 to 2020, the concentration of DIP in the BS during autumn increased, while the content of Reac-P in sediments slightly decreased. Historical data indicate that P depletion in the BS is intensifying and expanding, primarily due to N enrichment and algal production. N enrichment alters the structure and composition of primary production, potentially exacerbating P depletion in the BS. Excessive N may have significant impacts on the P pool, potentially influencing the stability of future coastal ecosystems.

Subgraph-Aware Graph Kernel Neural Network for Link Prediction in Biological Networks.

Identifying links within biological networks is important in various biomedical applications. Recent studies have revealed that each node in a network may play a unique role in different links, but most link prediction methods overlook distinctive node roles, hindering the acquisition of effective link representations. Subgraph-based methods have been introduced as solutions but often ignore shared information among subgraphs. To address these limitations, we propose a Subgraph-aware Graph Kernel Neural Network (SubKNet) for link prediction in biological networks. Specifically, SubKNet extracts a subgraph for each node pair and feeds it into a graph kernel neural network, which decomposes each subgraph into a combination of trainable graph filters with diversity regularization for subgraph-aware representation learning. Additionally, node embeddings of the network are extracted as auxiliary information, aiding in distinguishing node pairs that share the same subgraph. Extensive experiments on five biological networks demonstrate that SubKNet outperforms baselines, including methods especially designed for biological networks and methods adapted to various networks. Further investigations confirm that employing graph filters to subgraphs helps to distinguish node roles in different subgraphs, and the inclusion of diversity regularization further enhances its capacity from diverse perspectives, generating effective link representations that contribute to more accurate link prediction.

Modern software and physical education: can online training enhance gym training?

BACKGROUND: This study discusses the effectiveness of a 12-week intervention aimed at improving squat jump and sprint performance among second-year sports students. METHODS: The students were randomly divided into experimental (n = 89) and control (n = 92) groups. In addition to gym training, students of the experimental group also underwent online PE training. The students' performance in Squat Jumps, 30 m sprint, and Progressive Aerobic Cardiovascular Endurance Run (PACER), as well as their situational motivation, were assessed before and after the intervention. Furthermore, the students assessed their physical activity weekly using self-reports. RESULTS: The implementation of online training has positively impacted intrinsic and identified motivation, as well as external regulation; however, it was less effective in reducing amotivation compared to traditional gym-based training. CONCLUSIONS: The findings of the study contribute to the data synthesis on the expediency of using modern software in physical education.

An In Vitro Colonic Fermentation Study of the Effects of Human Milk Oligosaccharides on Gut Microbiota and Short-Chain Fatty Acid Production in Infants Aged 0-6 Months.

The impact of five human milk oligosaccharides (HMOs)-2'-fucosyllactose (2FL), 3'-sialyllactose (3SL), 6'-sialyllactose (6SL), lacto-N-tetraose (LNT), and lacto-N-neotetraose (LNnT)-on the gut microbiota and short-chain fatty acid (SCFA) metabolites in infants aged 0-6 months was assessed through in vitro fermentation. Analyses of the influence of different HMOs on the composition and distribution of infant gut microbiota and on SCFA levels were conducted using 16S rRNA sequencing, quantitative real-time PCR (qPCR), and gas chromatography (GC), respectively. The findings indicated the crucial role of the initial microbiota composition in shaping fermentation outcomes. Fermentation maintained the dominant genera species in the intestine but influenced their abundance and distribution. Most of the 10 Bifidobacteria strains effectively utilized HMOs or their degradation products, particularly demonstrating proficiency in utilizing 2FL and sialylated HMOs compared to non-fucosylated neutral HMOs. Moreover, our study using B. infantis-dominant strains and B. breve-dominant strains as inocula revealed varying acetic acid levels produced by Bifidobacteria upon HMO degradation. Specifically, the B. infantis-dominant strain yielded notably higher acetic acid levels than the B. breve-dominant strain (p = 0.000), with minimal propionic and butyric acid production observed at fermentation's conclusion. These findings suggest the potential utilization of HMOs in developing microbiota-targeted foods for infants.

Light Enables the Cathodic Interface Reaction Reversibility in Solid-State Lithium-Oxygen Batteries.

Limited triple-phase boundaries arising from the accumulation of solid discharge product(s) in solid-state cathodes (SSCs) pose a challenge to high-property solid-state lithium-oxygen batteries (SSLOBs). Light-assisted SSLOBs have been gradually explored as an ingenious system; however, the fundamental mechanisms of the SSCs interface behavior remain unclear. Here, we discovered that light assistance can enhance the fast inner-sphere charge transfer in SSCs and regulate the discharge products with spherical particles generated via the surface growth model. Moreover, the high photoelectron excitation and transportation capabilities of SSCs can retard cathodic catalytic decay by avoiding structural degradation of the cathode with a reduced charge voltage. The light-induced SSLOBs exhibited excellent stability (170 cycles) with a low discharge-charge polarization overpotential (0.27 V). Furthermore, transparent SSLOBs with exceptional flexibility, mechanical stability, and multiform shapes were fabricated for theory-to-practical applications in sunlight-induced batteries. Our study opens new opportunities for the introduction of solar energy into energy storage systems.

Ion-Dipole-Interaction-Induced Encapsulation of Free Residual Solvent for Long-Cycle Solid-State Lithium Metal Batteries.

Owing to high ionic conductivity and mechanical strength, poly(vinylidene fluoride) (PVDF) electrolytes have attracted increasing attention for solid-state lithium batteries, but highly reactive residual solvents severely plague cycling stability. Herein, we report a free-solvent-capturing strategy triggered by reinforced ion-dipole interactions between Li+ and residual solvent molecules. Lithium difluoro(oxalato)borate (LiDFOB) salt additive with electron-withdrawing capability serves as a redistributor of the Li+ electropositive state, which offers more binding sites for residual solvents. Benefiting from the modified coordination environment, the kinetically stable anion-derived interphases are preferentially formed, effectively mitigating the interfacial side reactions between the electrodes and electrolytes. As a result, the assembled solid-state battery shows a lifetime of over 2000 cycles with an average Coulombic efficiency of 99.9% and capacity retention of 80%. Our discovery sheds fresh light on the targeted regulation of the reactive residual solvent to extend the cycle life of solid-state batteries.

Lattice-Gradient Perovskite KTaO3 Films for an Ultrastable and Low-Dose X-Ray Detector.

Conventional indirect X-ray detectors employ scintillating phosphors to convert X-ray photons into photodiode-detectable visible photons, leading to low conversion efficiencies, low spatial resolutions, and optical crosstalk. Consequently, X-ray detectors that directly convert photons into electric signals have long been desired for high-performance medical imaging and industrial inspection. Although emerging hybrid inorganic-organic halide perovskites, such as CH3 NH3 PbI3 and CH3 NH3 PbBr3 , exhibit high sensitivity, they have salient drawbacks including structural instability, ion motion, and the use of toxic Pb. Here, this work reports an ultrastable, low-dose X-ray detector comprising KTaO3 perovskite films epitaxially grown on a Nb-doped strontium titanate substrate using a low-cost solution method. The detector exhibits a stable photocurrent under high-dose irradiation, high-temperature (200 °C), and aqueous conditions. Moreover, the prototype KTaO3 -film-based detector exhibits a 150-fold higher sensitivity (3150 µC Gyair -1 cm-2 ) and 150-fold lower detection limit (<40 nGyair s-1 ) than those of commercial α-Se-based direct detectors. Systematic investigations reveal that the high stability of the detector originates from the strong covalent bonds within the KTaO3 film, whereas the low detection limit is due to a lattice-gradient-driven built-in electric field and the high insulating property of KTaO3 film. This study unveils a new path toward the fabrication of green, stable, and low-dose X-ray detectors using oxide perovskite films, which have significant application potential in medical imaging and security operations.

The Effectiveness of White Light Endoscopy Combined With Narrow Band Imaging Technique Using Ni Classification in Detecting Early Laryngeal Carcinoma in 114 Patients: Our Clinical Experience.

INTRODUCTION: By displaying tumor-specific neoangiogenesis, narrow band imaging (NBI), a novel imaging approach, enhances the diagnosis of head and neck cancers and makes it more accurate OBJECTIVE: To determine the effect of NBI in combination with white light endoscopy (WLE) for diagnosis of preneoplastic or neoplastic laryngeal cancers according to Ni classification and to conclude if higher Ni classification and tumor stage are related. METHODS: We enrolled 114 patients with various laryngeal cancer between December 2018 and June 2021. Patients were examined with WLE and NBI. Squamous cell carcinoma (SCC) accounted for 46 cases, benign lesions 30 cases, and nondysplastic, low-grade, and severe dysplasias for 38 cases. Based on characteristics of the intraepithelial papillary capillary loop (IPCL), endoscopic NBI results were divided into five categories (I, II, III, IV, and V). Type I-IV are regarded to be benign, while type V is considered to be cancerous. An incisional biopsy was conducted to assess histopathology, and the histopathology was compared to the NBI results. We assessed the negative predictive value (NPV), positive predictive value (PPV), specificity, and sensitivity for WLE alone and WLE combined with NBI. Analyses were conducted using SPSS software version 26. RESULTS: The WLE combined with NBI showed excellent sensitivity (96%) compared to WLE (86.4%). Specificity was higher in the WLE combined with NBI (96.4%) than WLE alone (91.7%). WLE combined with NBI saw a NPV of 89% as compared with WLE with 88%. WLE and WLE in combination with NBI, recorded a PPV of 90% and 98%, respectively. CONCLUSION: The accuracy of detecting laryngeal cancer increases when WLE and NBI are combined. Combined NBI with WLE remains highly sensitive to early glottis cancer. Accuracy of preoperative NBI was high. In the diagnosis of laryngeal cancer, a higher Ni classification closely correlates with the late stages of the glottis tumor.

The effect of fission products Xe and Cs on the thermal conductivity of the U3Si2lattice: a first-principles study.

In the past decades, uranium silicide (U3Si2) as a promising accident tolerant fuel (ATF) has drawn considerable attention in the field of nuclear physics. In comparison with traditional nuclear fuel (UO2), the U3Si2has higher thermal conductivity and uranium density, thereby resulting in lower centerline temperatures and better fuel economy. However, during the nuclear fission reaction, some unexpected fission products, such as Xe and Cs, are released and form the defective states. In this study, we explore the influence of Xe and Cs on the thermal conductivity of the U3Si2lattice from 200 to 1500 K using density functional theory calculations combined with Boltzmann transport equation. Our results reveal that the lattice and electronic thermal conductivities of defective U3Si2are reduced at a constant temperature, as compared with that of ideal system, thus resulting in a decrease of the total thermal conductivity. In the case of Cs occupation at U1 site, the total thermal conductivity (4.42 W mK-1) is decreased by ∼56% at 300 K, as compared with the value of 9.99 W mK-1for ideal system. With U1 and Si sites being occupied by Xe, the total thermal conductivities (4.45 and 6.52 W mK-1) are decreased by ∼55% and 35% at 300 K, respectively. The presented results suggest that the U3Si2has potential as a promising ATF at high temperatures.

Multifocal Raman Spectrophotometer for Examining Drug-Induced and Chemical-Induced Cellular Changes in 3D Cell Spheroids.

Cell spheroids offer alternative in vitro cell models to monolayer cultured cells because they express complexities similar to those of in vivo tissues, such as cellular responses to drugs and chemicals. Raman spectroscopy emerged as a powerful analytical tool for detecting chemical changes in living cells because it nondestructively provides vibrational information regarding a target. Although multiple iterations are required in drug screening to determine drugs to treat cell spheroids and assess the inter-spheroid heterogeneity, current Raman applications used in spheroids analysis allow the observation of only a few spheroids owing to the low throughput of Raman spectroscopy. In this study, we developed a multifocal Raman spectrophotometer that enables simultaneous analysis of multiple spheroids in separate wells of a regular 96-well plate. By utilizing 96 focal spots excitation and parallel signal collection, our system can improve the throughput by approximately 2 orders of magnitude compared to a conventional single-focus Raman microscope. The Raman spectra of HeLa cell spheroids treated with anticancer drugs and HepG2 cell spheroids treated with free fatty acids were measured simultaneously, and concentration-dependent cellular responses were observed in both studies. Using the multifocal Raman spectrophotometer, we rapidly observed chemical changes in spheroids, and thus, this system can facilitate the application of Raman spectroscopy in analyzing the cellular responses of spheroids.

Pan-Cancer Identification of Prognostic-Associated Metabolic Pathways.

Metabolic dysregulation has been reported involving in the clinical outcomes of multiple cancers. However, systematical identification of the impact of metabolic pathways on cancer prognosis is still lacking. Here, we performed a pan-cancer analysis of popular metabolic checkpoint genes and pathways with cancer prognosis by integrating information of clinical survival with gene expression and pathway activity in multiple cancer patients. By discarding the effects of age and sex, we revealed extensive and significant associations between the survival of cancer patients and the expression of metabolic checkpoint genes, as well as the activities of three primary metabolic pathways: amino acid metabolism, carbohydrate metabolism, lipid metabolism, and eight nonprimary metabolic pathways. Among multiple cancers, we found the survival of kidney renal clear cell carcinoma and low-grade glioma exhibit high metabolic dependence. Our work systematically assesses the impact of metabolic checkpoint genes and pathways on cancer prognosis, providing clues for further study of cancer diagnosis and therapy.

The Efficacy of REG Proteins as a Diagnostic Biomarker for Pancreatic Cancer: a Meta-Analysis.

BACKGROUND: Regenerating gene (REG) family proteins play a pivotal role in cell proliferation, tissue regeneration, and tumor metastasis. Recent studies have concentrated on the role of REG proteins in pancreatic cancer, but the results remain controversial. In this study, a meta-analysis was performed to evaluate the precise diagnostic value of REG proteins in pancreatic cancer. METHODS: A search was conducted in PubMed, Medline, Embase, Cochrane Library, Chinese National Knowledge Infrastructure (CNKI), Biomedical Literature Database (CBM), and WANFANG Data up to May 5, 2021. The QUADAS-2 tool was used to evaluate the quality of the included studies. The statistical analysis of the diagnostic tests was conducted using RevMan5 and Meta-Disc 1.4. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and their 95% confidence intervals (95% CIs) were calculated from each eligible study. RESULTS: The meta-analysis included 15 articles containing 796 patients and 584 controls. The pooled sensitivity was 0.71 (95% CI: 0.67 - 0.74), the pooled specificity was 0.73 (95% CI: 0.70 - 0.76), and the pooled DOR was 11.35 (95% CI: 5.92 - 21.77), respectively. The overall area under the receiver operating characteristic curve (AUC) was 0.84. Spearman's correlation coefficient was 0.34 (p = 0.221). For the subgroup analysis, the REG4 protein showed higher diagnostic accuracy compared with the other REG proteins. CONCLUSIONS: REG proteins have moderate diagnostic accuracy in pancreatic cancer. Further well-designed studies with larger sample sizes and clinical application are needed to validate the results of this meta-analysis.

An electrochemical biosensor based on network-like DNA nanoprobes for detection of mesenchymal circulating tumor cells.

The identification and detection of mesenchymal circulating tumor cells （mCTCs） is important for early warning of tumor metastasis. The majority of conventional detection methods for CTCs rely on the recognition of epithelial biomarkers, which is technically challenging for detecting CTCs with epithelial-mesenchymal transition (EMT)-induced phenotypic alteration. In this work, we have constructed a label-free biosensor for sensitive electrochemical assay of mCTCs. In our design, the capture probe can recognize the vimentin overexpressed on the surface of mCTCs with high specificity. Meantime, the network-like DNA nanoprobes with multiple G-quadruplex/hemin complexes and multiple cholesterol molecules can be grafted to the cell surface based on the high affinity between cholesterol molecules and cell membrane. Owing to the mimic horseradish peroxidase of G-quadruplex/hemin complexes, strong electrochemical responses will be obtained for sensitive quantification of mCTCs with a detection limit of 8 cell mL-1. Moreover, the biosensor can effectively overcome the interference of vimentin negative cells or secretory vimentin, and realize the recovery tests in whole blood with high accuracy, thereby may further promoting the diagnosis and personalized treatment of cancer in clinic.

The preventive effect of PNF stretching exercise on sports injuries in physical education based on IoT data monitoring.

In physical education, in order to prevent sports injuries of students, it is necessary to study and build a set of physical education Internet of Things data monitoring training system to prevent sports injuries of students. This system is mainly composed of sensors, smart phones and cloud servers. Wearable devices equipped with sensors are used to complete data acquisition and transmission by means of the Internet of Things system, and relevant parameters are sorted and monitored by combining data analysis technology. The system makes a more in-depth, comprehensive and accurate analysis and processing of the collected data, so as to better evaluate the status and quality of students' sports, find out the existing problems in time, and put forward the corresponding solutions. By analyzing students' sports data and health data, the system generates personalized training programs, including training intensity, training time, training frequency and other parameters, so as to meet the needs and actual conditions of different students and avoid sports injuries caused by overtraining. This system can better analyze and process the collected data, provide teachers with more comprehensive and in-depth assessment and monitoring of students' sports status, and provide students with more personalized and scientific training programs, so as to effectively prevent the occurrence of students' sports injuries.

Iodide-Enhanced Perovskite Nanozyme-Based Colorimetric Platform for Detection of Urinary Nuclear Matrix Protein 22.

In the last decade, perovskite nanocrystals (PNCs) have brought extensive thinking owing to their excellent optical properties. Recently, we have uncovered the peroxidase-like activity of PNCs and used this for detecting many small molecules; however, the low enzymatic activity makes them unsuitable for fluorescence analysis, which is easily disturbed by the autofluorescence of biological media. This greatly limits their application in bioanalysis. Thus, the development of a method to facilely modulate the activity of PNCs for the instrument-free colorimetric detection is highly desirable. Herein, we demonstrated an iodide-enhanced perovskite nanozyme-based colorimetric platform for the visual assay of urinary nuclear matrix protein 22 (NMP22), a typical biomarker for the diagnosis of bladder cancer. We discovered that halogen could regulate the activity of perovskite nanozymes through a simple anion replacement reaction. Experimental analysis suggested that CsPbI3 nanocrystals (NCs) displayed 24-fold higher catalytic efficiency than classical CsPbBr3 NCs. As a proof-of-concept assay, the CsPbI3 NCs could be explored into an immunoassay for the detection of NMP22 in clinical urine specimens, resulting in a low detection limit of 0.03 U/mL. This iodide-enhanced immunoassay deepens our understanding of perovskite nanozymes and also provides great potential for bioanalysis.