Predicting the efficiency of arsenic immobilization in soils by biochar using machine learning.

Arsenic (As) pollution in soils is a pervasive environmental issue. Biochar immobilization offers a promising solution for addressing soil As contamination. The efficiency of biochar in immobilizing As in soils primarily hinges on the characteristics of both the soil and the biochar. However, the influence of a specific property on As immobilization varies among different studies, and the development and application of arsenic passivation materials based on biochar often rely on empirical knowledge. To enhance immobilization efficiency and reduce labor and time costs, a machine learning (ML) model was employed to predict As immobilization efficiency before biochar application. In this study, we collected a dataset comprising 182 data points on As immobilization efficiency from 17 publications to construct three ML models. The results demonstrated that the random forest (RF) model outperformed gradient boost regression tree and support vector regression models in predictive performance. Relative importance analysis and partial dependence plots based on the RF model were conducted to identify the most crucial factors influencing As immobilization. These findings highlighted the significant roles of biochar application time and biochar pH in As immobilization efficiency in soils. Furthermore, the study revealed that Fe-modified biochar exhibited a substantial improvement in As immobilization. These insights can facilitate targeted biochar property design and optimization of biochar application conditions to enhance As immobilization efficiency.

Efficacy and safety of ultrasound-guided percutaneous radiofrequency ablation for synovial hyperplasia.

PURPOSE: This study aimed to investigate the efficacy and safety of ultrasound-guided percutaneous radiofrequency ablation (RFA) for the treatment of synovial hyperplasia in the knee joints of antigen-induced arthritis (AIA) model rabbits. METHODS: Forty Japanese large-eared white rabbits were divided into AIA and control groups. After successful induction of the AIA model, the knee joints were randomly assigned to RFA and non-RFA groups. The RFA group underwent ultrasound-guided RFA to treat synovial hyperplasia in the knee joint. Dynamic observation of various detection indices was conducted to evaluate the safety and effectiveness of the RFA procedure. RESULTS: Successful synovial ablation was achieved in the RFA group, with no intraoperative or perioperative mortality. Postoperative the circumference of the knee joint reached a peak before decreasing in the third week after surgery. The incidence and diameter of postoperative skin ulcers were not significantly different compared to the non-RFA group (p > .05). Anatomical examination revealed an intact intermuscular fascia around the ablated area in the RFA group. The ablated synovial tissue initially presented as a white mass, which subsequently liquefied into a milky white viscous fluid. Gross articular cartilage was observed, along with liquefied necrosis of the synovium on pathological histology and infiltration of inflammatory cells in the surrounding soft tissue. CONCLUSION: The experimental results demonstrated that ultrasound-guided RFA of the knee in the treatment of synovial hyperplasia in AIA model animals was both effective and safe.

Effects of recreational team sports on the metabolic health, body composition and physical fitness parameters of overweight and obese populations: A systematic review.

This systematic review aims to provide a summary of the results from individual studies that specifically focused on overweight or obese populations, regardless of age or sex. The goal is to determine the effects of structured recreational team sports interventions (TSG) on metabolic health, body composition and physical fitness parameters when compared to passive or active control groups. This study adhered to the PRISMA guidelines for reporting a systematic review. A thorough examination of relevant literature was conducted on November 06, 2023, using three prominent databases: PubMed, Scopus, and the Web of Science. Inclusion criteria considered overweight (e.g., BMI 25.0-29.9 kg/m2) and obese (e.g., BMI > 30 kg/m2) populations exposed to training interventions using recreational team sports, while the comparator group consisted of the same populations not exposed to exercise (passive controls) or exposed to alternative training methods. The primary outcomes of interest were metabolic health parameters (glucose, waist circumference, blood pressure, cholesterol, triglycerides), body composition (e.g., fat mass, lean mass), as well as physical fitness parameters (e.g., aerobic fitness, muscular fitness). Only studies with two- or multi-arm designs, whether randomized or not, were eligible for inclusion. The PEDro scale was used to assess the methodological bias of the included studies. Out of the initial 275 titles retrieved, we deemed ten eligible for our study. In terms of body composition, TSG demonstrated a significant decrease in body mass index across three studies (-2.3 to -5.1%) and a significant reduction in waist circumference in four studies (-4.6% to -8.4%). Regarding blood pressure, TSG exhibited a significant decrease in systolic blood pressure in two studies (-3.9% to -8.3%), while diastolic blood pressure showed a significant decrease in only one study (-7.3%). Cholesterol levels saw a significant decrease in TSG in three studies (-7.0% to -9.7%), and triglyceride levels showed a significant reduction in four studies (-16.4% to -20.1%). In terms of aerobic fitness, TSG demonstrated within-group improvements in the field-based tests in three studies (8.1% to 79.0%), and within-group improvements in maximal oxygen uptake in four studies (6.5% to 31.0%), with significant favoring of TSG in most studies. Overall, TSG demonstrated significant benefits for overweight and obese populations compared to the control group, particularly in terms of improvements in body mass index, systolic blood pressures, cholesterol and triglyceride levels, and aerobic fitness. Future research ought to concentrate on tailoring responses to varying training volumes on an individualized basis.

Exploring the role of cellular senescence in cancer prognosis across multiple tumor types.

Background: Cellular senescence is a common biological process with a well-established link to cancer. However, the impact of cellular senescence on tumor progression remains unclear. To investigate this relationship, we utilized transcriptomic data from a senescence gene set to explore the connection between senescence and cancer prognosis. Methods: We developed the senescence score by the Least Absolute Shrinkage and Selection Operator (LASSO) Cox model. We obtained transcriptomic information of the senescence gene set from The Cancer Genome Atlas (TCGA) program. Additionally, we created a nomogram that integrates these senescence scores with clinical characteristics, providing a more comprehensive tool for prognosis evaluation. Results: We calculated the senescence score based on the expression level of 42 senescence-related genes. We established the nomogram based on the senescence score and clinical characteristics. The senescence score showed a positive correlation with epithelial-to-mesenchymal transition, cell cycle, and glycolysis, and a negative correlation with autophagy. Furthermore, we carried out Gene Ontology (GO) analysis to explore the signaling pathways and biological process in different senescence score groups. Conclusions: The senescence score, a novel tool constructed in this study, shows promise in predicting survival outcomes across various cancer types. These findings not only highlight the complex interplay between senescence and cancer but also indicate that cellular senescence might serve as a biomarker for tumor prognosis.

Synthesis of non-modified near-infrared carbon dots for hypochlorite detection and cell membrane imaging.

Devising carbon dots with long wavelength emission (red light or near infrared), high selectivity and good bio-compatibility is critical in fluorescence detection and imaging, but achieving this goal remains a great challenge. Herein, near-infrared emissive carbon dots (NIR-CDs) with obvious emission characteristic of 653 nm were synthesized through hydrothermally treatment of toluidine bule and gallic acid. Noticeably, the NIR-CDs exhibited excellent selectivity and sensitivity to hypochlorite (ClO-), and the limit of detection is as low as 42.7 nM. The selective recognition reaction between ClO- and the surface functional groups of NIR-CDs inhibits the fluorescence from NIR-CDs. The quenching mechanism was confirmed by fluorescence lifetime decays, FT-IR spectroscopy and UV-vis absorption spectra. More remarkably, the NIR-CDs have rich hydrophilic groups showed lower cytotoxicity, excellent bio-compatibility and specific cell membrane localization ability. The established spectrofluorometric method based on NIR-CDs has been used to determination of ClO- level in tap water sample, the recoveries were 97.7 %-103.3 %. In addition, the NIR-CDs also has been successfully applied for the imaging of cell membrane. The study provides a novel idea for developing NIR ClO- probe as well as cell membrane localization probe based on CDs, which present bright prospects in real water samples monitoring and cell membrane imaging.

Evaluating the impact of a combined aerobic and strength training intervention on the physical performance of male Chinese People's Liberation Army air force pilots.

This study aimed to assess the impact of a 16-week combined training program on the physical performance of 20 male Air Force pilots, with an average age of 31.87 ± 2.75 years, body mass of 76.33 ± 0.79 kg, and height of 175.55 ± 3.65 cm. This intervention encompassed both aerobic and strength training, involving six weekly training sessions. The participants were categorized into two groups based on their initial physical performance levels to explore potential baseline influences on post-intervention adaptations. The study measured changes in estimated maximal oxygen uptake (VO2 max), maximal strength, muscular endurance, and long jump performance before and after the training program. Repeated measures ANOVA revealed significant differences over time in the V ˙ O2 max (F = 86.898; p < 0.001; η p 2  = 0.821), handgrip strength right hand (F = 160.480; p < 0.001; η p 2  = 0.894), handgrip strength left hand (F = 102.196; p < 0.001; η p 2  = 0.843), squat maximal strength (F = 525.725; p < 0.001; η p 2  = 0.965), push-ups (F = 337.197; p < 0.001; η p 2  = 0.974), sit up (F = 252.500; p < 0.001; η p 2  = 0.930) and standing long jump (F = 521.714; p < 0.001; η p 2  = 0.965). In conclusion, the 16-week combined training regimen significantly enhanced the physical performance of Air Force pilots, regardless of their initial performance levels.

Enhancing Kinase Activity Detection with a Programmable Lanthanide Metal-Organic Framework via ATP-to-ADP Conversion.

Precise modulation of host-guest interactions between programmable Ln-MOFs (lanthanide metal-organic frameworks) and phosphate analytes holds immense promise for enabling novel functionalities in biosensing. However, the intricate relationship between these functionalities and structures remains largely elusive. Understanding this correlation is crucial for advancing the rational design of fluorescent biosensor technology. Presently, there exists a large research gap concerning the utilization of Ln-MOFsto monitor the conversion of ATP to ADP, which poses a limitation for kinase detection. In this work, we delve into the potential of Ln-MOFs to amplify the fluorescence response during the kinase-mediated ATP-to-ADP conversion. Six Eu-MOFs were synthesized and Eu-TPTC ([1,1':4',1″]-terphenyl-3,3'',5,5''-tetracarboxylic acid) was selected as a ratiometric fluorescent probe, which is most suitable for high-precision detection of creatine kinase activity through the differential response from ATP to ADP. The molecular -level mechanism was confirmed by density functional theory. Furthermore, a simple paper chip-based platform was constructed to realize the fast (20 min) and sensitive (limit of detection is 0.34 U/L) creatine kinase activity detection in biological samples. Ln-MOF-phosphate interactions offer promising avenues for kinase activity assays and hold the potential for precise customization of analytical chemistry.

Programmable Lanthanide Metal-Organic Framework for Ultra-Efficient Nucleic Acids Extraction and Interaction Analysis.

Efficient, mild, and reversible adsorption of nucleic acids onto nanomaterials represents a promising analytical approach for medical diagnosis. However, there is a scarcity of efficient and reversible nucleic acid adsorption nanomaterials. Additionally, the lack of comprehension of the molecular mechanisms governing their interactions poses significant challenges. These issues hinder the rational design and analytical applications of the nanomaterials. Herein, we propose an ultra-efficient nucleic acid affinity nanomaterial based on programmable lanthanide metal-organic frameworks (Ln-MOFs). Through experiments and density functional theory calculations, a rational design guideline for nucleic acid affinity of Ln-MOF was proposed, and a modular and flexible preparation scheme was provided. Then, Er-TPA (terephthalic acid) MOF emerged as the optimal candidate due to its pore size-independent adsorption and desorption capabilities for nucleic acids, enabling ultra-efficient adsorption (about 150% mass ratio) within 1 min. Furthermore, we elucidate the molecular-level mechanisms underlying the Ln-MOF adsorption of single- and double-stranded DNA and G4 structures. The affinity nanomaterial based on Ln-MOF exhibits robust nucleic acid extraction capability (4-fold higher than commercial reagent kits) and enables mild and reversible CRISPR/Cas9 functional regulation. This method holds significant promise for broad application in DNA/RNA liquid biopsy and gene editing, facilitating breakthroughs in analytical chemistry, pharmacy, and medical research.

Integrated Lipidomics and Transcriptomics Analyses Reveal Key Regulators of Fat Deposition in Different Adipose Tissues of Geese (Anser cygnoides).

The fat deposition of different adipose tissues is widely recognized as correlated, with distinct effects on meat quality traits and reproductive performance in poultry. In this study, we utilized lipidomics and transcriptomics analyses to investigate the heterogeneity and regulators of intramuscular fat (IMF), abdominal fat (AF), and subcutaneous fat (SF) in geese. Lipidomic profiling revealed 165, 129, and 77 differential lipid molecules (DLMs) between AF vs. IMF, SF vs. IMF, and SF vs. AF, respectively, with 47 common DLMs identified between AF vs. IMF and SF vs. IMF. Transcriptomic analysis identified 3369, 5758, and 131 differentially expressed genes (DEGs) between AF vs. IMF, SF vs. IMF, and SF vs. AF, respectively, with 2510 common DEGs identified between AF vs. IMF and SF vs. IMF. The KEGG results indicate that DLMs were predominantly enriched in glycerophospholipid and glycerolipid metabolism pathways, while DEGs were primarily enriched in metabolic pathways. Pearson correlation analysis identified FABP4, LPL, PLCB1, DSE, and PDE5A as potential factors influencing fat deposition. This study elucidates the heterogeneity and regulatory factors of different adipose tissues in geese, offering new insights for targeted improvements in goose meat quality and production efficiency.

Effects of soy protein-rich meals on muscle health of older adults in long-term care: A randomized clinical trial.

OBJECTIVE: This study investigated the effects of a soy protein-rich meal intervention on the muscle health of older adults in long-term care facilities. METHODS: A 12-week single-center randomized controlled trial with a control-group and open-label design was conducted. Eighty-four older adults from a long-term care facility participated in the study. The chefs at the facility cooked three meals using soy protein-rich recipes designed by dieticians. For 12 weeks, the intervention group participants consumed three meals with 30 g of soy protein (10 g/meal) per day, and the control group participants maintained their habitual diets. RESULTS: The 84 participants (mean age, 84.9 ± 7.0 years; 61.9% female) were randomly assigned to an intervention group (43 participants) and a control group (41 participants). The intervention group exhibited significant increases in several lean mass indicators, namely soft lean mass (mean, 1.43 kg; 95% confidence interval [CI]: 0.20-1.65 kg), skeletal muscle mass (mean, 1.20 kg; 95% CI: 0.43-1.96 kg), appendicular skeletal muscle mass (mean, 0.79 kg; 95% CI: 0.07-1.52 kg), and skeletal muscle index (mean, 0.37 kg/m2; 95% CI: 0.05-0.68 kg/m2) (all P < 0.05). These changes were not observed in the control group (all P > 0.05). Notably, calf circumference decreased significantly in the control group (mean, -0.98 cm; 95% CI: -1.61 to -0.36 cm) but was maintained in the intervention group. The differences in the calf circumference and 6-m walk performance of the two groups were significant (P < 0.05). CONCLUSIONS: The 12-week soy protein-rich meal intervention improved the muscle mass and 6-m walk performance of older adults in a long-term care facility.

Serum metabolic changes link metal mixture exposures to vascular endothelial inflammation in residents living surrounding rivers near abandoned lead-zinc mines.

Metal exposure is associated with vascular endothelial inflammation, an early pathological phenotype of atherosclerotic cardiovascular events. However, the underlying mechanism linking exposure, metabolic changes, and outcomes remains unclear. We aimed to investigate the metabolic changes underlying the associations of chronic exposure to metal mixtures with vascular endothelial inflammation. We recruited 960 adults aged 20-75 years from residential areas surrounding rivers near abandoned lead-zinc mine and classified them into river area and non-river area exposure groups. Urine levels of 25 metals, Framingham risk score (FRS), and serum concentrations of intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), as biomarkers of vascular endothelial inflammation, were assessed. A "meet-in-the-middle" approach was applied to identify causal intermediate metabolites and metabolic pathways linking metal exposure to vascular endothelial inflammation in representative metabolic samples from 64 participants. Compared to the non-river area exposure group, the river area exposure group had significantly greater urine concentrations of chromium, copper, cadmium, and lead; lower urine concentrations of selenium; elevated FRS; and increased concentrations of ICAM-1 and VCAM-1. In total, 38 differentially abundant metabolites were identified between the river area and non-river area exposure groups. Among them, 25 metabolites were significantly associated with FRS, 8 metabolites with ICAM-1 expression, and 10 metabolites with VCAM-1 expression. Furthermore, fructose, ornithine, alpha-ketoglutaric acid, urea, and cytidine monophosphate, are potential mediators of the relationship between metal exposure and vascular endothelial inflammation. Additionally, the metabolic changes underlying these effects included changes in arginine and proline metabolism, pyrimidine metabolism, starch and sucrose metabolism, galactose metabolism, arginine biosynthesis, and alanine, aspartate, and glutamate metabolism, suggesting the disturbance of amino acid metabolism, the tricarboxylic acid cycle, nucleotide metabolism, and glycolysis. Overall, our results reveal biomechanisms that may link chronic exposure to multiple metals with vascular endothelial inflammation and elevated cardiovascular risk.

A novel prognostic signature related to programmed cell death in osteosarcoma.

Background: Osteosarcoma primarily affects children and adolescents, with current clinical treatments often resulting in poor prognosis. There has been growing evidence linking programmed cell death (PCD) to the occurrence and progression of tumors. This study aims to enhance the accuracy of OS prognosis assessment by identifying PCD-related prognostic risk genes, constructing a PCD-based OS prognostic risk model, and characterizing the function of genes within this model. Method: We retrieved osteosarcoma patient samples from TARGET and GEO databases, and manually curated literature to summarize 15 forms of programmed cell death. We collated 1621 PCD genes from literature sources as well as databases such as KEGG and GSEA. To construct our model, we integrated ten machine learning methods including Enet, Ridge, RSF, CoxBoost, plsRcox, survivalSVM, Lasso, SuperPC, StepCox, and GBM. The optimal model was chosen based on the average C-index, and named Osteosarcoma Programmed Cell Death Score (OS-PCDS). To validate the predictive performance of our model across different datasets, we employed three independent GEO validation sets. Moreover, we assessed mRNA and protein expression levels of the genes included in our model, and investigated their impact on proliferation, migration, and apoptosis of osteosarcoma cells by gene knockdown experiments. Result: In our extensive analysis, we identified 30 prognostic risk genes associated with programmed cell death (PCD) in osteosarcoma (OS). To assess the predictive power of these genes, we computed the C-index for various combinations. The model that employed the random survival forest (RSF) algorithm demonstrated superior predictive performance, significantly outperforming traditional approaches. This optimal model included five key genes: MTM1, MLH1, CLTCL1, EDIL3, and SQLE. To validate the relevance of these genes, we analyzed their mRNA and protein expression levels, revealing significant disparities between osteosarcoma cells and normal tissue cells. Specifically, the expression levels of these genes were markedly altered in OS cells, suggesting their critical role in tumor progression. Further functional validation was performed through gene knockdown experiments in U2OS cells. Knockdown of three of these genes-CLTCL1, EDIL3, and SQLE-resulted in substantial changes in proliferation rate, migration capacity, and apoptosis rate of osteosarcoma cells. These findings underscore the pivotal roles of these genes in the pathophysiology of osteosarcoma and highlight their potential as therapeutic targets. Conclusion: The five genes constituting the OS-PCDS model-CLTCL1, MTM1, MLH1, EDIL3, and SQLE-were found to significantly impact the proliferation, migration, and apoptosis of osteosarcoma cells, highlighting their potential as key prognostic markers and therapeutic targets. OS-PCDS enables accurate evaluation of the prognosis in patients with osteosarcoma.

Microdosing Plyometric Training Enhances Jumping Performance, Reactive Strength Index, and Acceleration among Youth Soccer Players: A Randomized Controlled Study Design.

Microdosing can facilitate better accommodation to the training stimulus while aligning with the scheduling needs of teams. In this study, the effectiveness of microdosing exposure was investigated by comparing the effects of microdosing plyometric jump training (microPJT) with those of regular plyometric jump training (regPJT) and a control group not exposed to plyometric training. The comparison focused on the effects on jumping performance, reactive strength index (RSI), and acceleration over a 10-meter distance. Fifty-two male youth soccer players (16.3 ± 0.6 years old) from under-17 teams participated in a randomized controlled study, with interventions lasting 8 weeks. Assessments were conducted twice, before and after the intervention, measuring squat jump (SJ), countermovement jump (CMJ), RSI during drop jumps, and acceleration in a 10-meter sprint test. The regPJT group completed 34 bilateral jumps and 48 unilateral jumps per week over two weekly sessions, totaling 82 jumps. Conversely, the microPJT group performed 17 bilateral jumps and 24 unilateral jumps weekly over 4 sessions week, totaling 41 jumps. Significant interactions between groups and time were observed concerning SJ (p < 0.001; η2= 0.282), CMJ (p < 0.001; η2= 0.368), RSI (p < 0.001; η2= 0.400) and 10-m sprint time (p < 0.001; η2 = 0.317). Between-group analysis indicated that both the microPJT (p < 0.001) and regPJT (p < 0.001) groups exhibited significant better results compared to the control group in post-intervention evaluation of SJ, CMJ, RSI and 10-m sprint time, while no significant differences were found between experimental groups (p > 0.050). In conclusion, this study has revealed that both microPJT and regPJT are equally effective in enhancing jumping performance and acceleration time in soccer players. This suggests that a smaller training volume, distributed more frequently across the week, can effectively induce improvements in soccer players.

Small-Sided Soccer Games Promote Greater Adaptations on Vertical Jump and Change-of-Direction Deficit and Similar Adaptations in Aerobic Capacity than High-Intensity Interval Training in Females.

The objective of this study was to compare the effectiveness of both small-sided games (SSG) and short interval running-based high-intensity interval training (HIIT) programs over an 8-week period in fostering adaptations in aerobic capacity, change-of-direction abilities, and jumping performances of youth female soccer players. The study involved 48 female youth participants under the age of 19, competing at the regional level, who took part in a randomized controlled trial. Participants were assigned to either the SSG group, the HIIT group, or a control group, which involved regular in-field sessions. Assessments were conducted at baseline and after the 8-week training intervention, measuring aerobic capacity using the 30-15 intermittent fitness test (VIFT), change of direction (COD) using the 5-0-5 test, and jumping performance using the countermovement jump test (CMJ). Time 5 group analysis revealed significant interactions in CMJ (p = 0.005; ηp2= 0.213) and VIFT (p < 0.001; ηp2 = 0.433), although no significant interaction were found in COD deficit (p = 0.246; ηp2 = 0.060). Within-group analysis revealed that SSG significantly improved CMJ (p < 0.001), COD deficit (p < 0.001), and VIFT (p < 0.001). HIIT group also significantly improved CMJ (p = 0.029), COD deficit (p = 0.001), and VIFT (p < 0.001). As conclusion, the study revealed that SSG promoted significantly improvements in VIFT, CMJ and COD deficit, being significantly better than control group, while HIIT was only significantly better than control in VIFT. SSG revealed to be effective approach for favoring key physical attributes of female soccer players, being an interesting and recommended training approach to increase the ecology of the training practice, while favoring physical positive adaptations.

Sex Influences the Extent of Physical Performance Adaptations in Response to Small-Sided Games and Running-Based High-Intensity Interval Training: A Parallel Study Design Involving Men and Women Soccer Players.

The aim of this study was two-fold: (i) to compare physical fitness adaptations following small-sided games (SSG) and running-based high-intensity interval training (HIIT), considering sex interactions; and (ii) to describe intra-individual variations of adaptations in both men and women developmental/trained soccer players over an 8-week randomized parallel study design involving 25 women and 27 men. Pre and post-intervention assessments included countermovement jump (CMJ), 10-meter linear sprint test, change-of-direction (COD) deficit, and final velocity at 30-15 Intermittent Fitness Test (VIFT). Significant interactions between time, groups and sex were found in 10-m sprint (F1,48 = 6.042; p = 0.018; ηp2 = 0.112). No significant interactions between time, groups and sex were found in CMJ (F F1,48 = 0.609; p = 0.439; ηp2 = 0.013), COD deficit (F F1,48 = 2.718; p = 0.106; ηp2 = 0.054) and VIFT (F F1,48 = 1.141; p = 0.291; ηp2 = 0.023). Significant interactions were found between time and sex in CMJ (F F1,48 = 29.342; p < 0.001; ηp2= 0.379), 10-m sprint (F F1,48 = 4.359; p = 0.042; ηp2 = 0.083), COD deficit (F F1,48 = 5.066; p = 0.029; ηp2= 0.095) and VIFT (F F1,48 = 11.248; p = 0.002; ηp2 = 0.190). In conclusion, this study suggests similar effects of HIIT in both sexes. However, for women, SSG may entail less efficacy and more inter-individual variability compared to men. Therefore, HIIT could potentially be a better solution for women, whereas both training approaches were equally effective in men.

Jumping Interval Training: An Effective Training Method for Enhancing Anaerobic, Aerobic, and Jumping Performances in Aerobic Gymnastics.

The aim of this study was to compare the effects of jumping interval training (JIT) and running high-intensity interval training (HIIT) on the aerobic, anaerobic and jumping performances of youth female aerobic gymnasts. A randomized controlled study was conducted over an 8-week period, involving 73 youth female athletes (16.2 ± 1.3 years old) of aerobic gymnastics. The study comprised two experimental groups (JIT and HIIT) and a control group. Participants in the experimental groups engaged in two additional training sessions per week alongside their regular training regimen, while the control group followed their usual training routine. Before and after the intervention period, gymnasts were assessed for their performance in the countermovement jump test (CMJ), the specific aerobic gymnastics anaerobic test (SAGAT) and the 20-m multistage fitness test. Significant interactions time × group were found in SAGAT (p < 0.001; = 0.495), CMJ (p < 0.001; = 0.338) and 20-m multistage fitness test (p < 0.001; = 0.500). The time × group analysis post-intervention revealed significantly lower scores in SAGAT for the control group compared to the JIT (p = 0.003) and HIIT (p = 0.034). Additionally, significantly higher scores were observed for the JIT group in the CMJ test compared to the HIIT (p = 0.020) and control (p = 0.028) groups following the intervention. Finally, the 20 m multistage fitness test post-intervention revealed significantly lower scores for the control group compared to JIT (p < 0.001) and HIIT (p < 0.001). Both JIT and HIIT are recommended training strategies to adopt in aerobic gymnastics for significantly improving the aerobic and anaerobic performances of athletes. However, JIT may be particularly relevant to use as it offers additional benefits in improving vertical jumping performances.

Antibiotics in Surface Sediments from the Anning River in Sichuan Province, China: Occurrence, Distribution, and Risk Assessment.

The occurrence, distribution, and ecological risk assessment of 36 antibiotics from five groups, including macrolides (MLs), fluoroquinolones (FQs), tetracyclines (TCs), amphenicols (APs), and sulfonamides (SAs), were investigated for the first time in the Anning River, Sichuan Province, China. The results show that antibiotics were widely present in the sediments of the Anning River, with a total of 22 antibiotics detected. FQs were among the most abundant antibiotics, followed by TCs, MLs, APs, and SAs. The total concentrations of antibiotics in surface sediments varied from 0.05 to 53.35 ng/g, with an average of 8.09 ng/g. Among these groups, MLs, FQs, and TCs emerged as the predominant classes of antibiotics. The midstream sediments showed the highest residual levels of antibiotics, with lower levels observed in the downstream and upstream sediments. Anthropogenic activities, such as human clinical practices and animal breeding, might be sources of antibiotics released into the river. An ecological risk assessment revealed that trimethoprim from the SA group exhibited high risks, and MLs showed medium risks in the Anning River, whereas most antibiotics presented minimal to low risks. This study provides valuable information on antibiotic pollution in the upstream region of the Yangtze River, and future management measures are needed for the Anning River.

The Diversity and Floristic Analysis of Rust Diseases in the Sanjiangyuan Forest Plants.

Between 2020 and 2023, rust fungus specimens were collected from the primary forested regions of the Sanjiangyuan area in Qinghai Province, resulting in over 300 samples. A taxonomic and phylogenetic study of the rust fungi from these forests was conducted using morphological and molecular biological techniques. The investigation identified rust fungi from 7 families, 12 genera, 56 species and varieties, including 10 new host records, 1 new record for China, and 2 novel species. The host plants involved belonged to 26 families, 48 genera, and 78 species. Pucciniaceae and Coleosporiaceae were the dominant families, with the genera Puccinia, Melampsora, and Gymnosporangium being prevalent. The rust fungi in the Sanjiangyuan forests showed a biogeographical affinity with the North Temperate Zone. Floristic comparisons revealed a higher similarity with rust fungi from Inner Mongolia, Gansu, and Tibet and a lower similarity with those from Hainan. An analysis of the life forms of rust fungus host plants indicated that herbaceous plants were the most common, followed by shrubs and trees. In different regions of Sanjiangyuan, rust fungi were found as follows: Golog Prefecture with 6 families, 9 genera, and 28 species; Yushu Prefecture with 5 families, 8 genera, and 31 species; Huangnan Prefecture with 5 families, 9 genera, and 26 species; and Hainan Prefecture with 4 families, 5 genera, and 10 species. The families Pucciniaceae, Melampsoraceae, and Coleosporiaceae were common across all four regions. Moreover, the families Rosaceae, Asteraceae, Ranunculaceae, Salicaceae, and Caprifoliaceae were shared among the host plants in these regions.

Robust Sensory Information Reconstruction and Classification With Augmented Spikes.

Sensory information recognition is primarily processed through the ventral and dorsal visual pathways in the primate brain visual system, which exhibits layered feature representations bearing a strong resemblance to convolutional neural networks (CNNs), encompassing reconstruction and classification. However, existing studies often treat these pathways as distinct entities, focusing individually on pattern reconstruction or classification tasks, overlooking a key feature of biological neurons, the fundamental units for neural computation of visual sensory information. Addressing these limitations, we introduce a unified framework for sensory information recognition with augmented spikes. By integrating pattern reconstruction and classification within a single framework, our approach not only accurately reconstructs multimodal sensory information but also provides precise classification through definitive labeling. Experimental evaluations conducted on various datasets including video scenes, static images, dynamic auditory scenes, and functional magnetic resonance imaging (fMRI) brain activities demonstrate that our framework delivers state-of-the-art pattern reconstruction quality and classification accuracy. The proposed framework enhances the biological realism of multimodal pattern recognition models, offering insights into how the primate brain visual system effectively accomplishes the reconstruction and classification tasks through the integration of ventral and dorsal pathways.

End-to-end learning strategy based on a frequency domain feature decoupling network emulator with joint probabilistic shaping and equalization for a 300-Gbit/s OAM mode division multiplexing transmission.

Mode coupling and device nonlinear impairment appear to be a long-standing challenge in the orbital angular momentum (OAM) mode division multiplexing (MDM) of intensity modulation direct detection (IM/DD) transmission systems. In this paper, we propose an end-to-end (E2E) learning strategy based on a frequency domain feature decoupling network (FDFDnet) emulator with joint probabilistic shaping (PS) and equalization for an OAM-MDM IM/DD transmission with three modes. Our FDFDnet emulator can accurately build a complex nonlinear model of an OAM-MDM system by separating the signal into features from different frequency domains. Furthermore, a FDFDnet-based E2E strategy for joint PS and equalization is presented with the aim of compensating the signal impairment for the OAM-MDM IM/DD system. An experiment is carried out on a 300 Gbit/s carrierless amplitude phase-32 (CAP-32) signal with three OAM modes over a 10 km ring-core fiber transmission, and the results show that the proposed FDFDnet emulator outperforms the traditional CGAN emulator, with improvements in the modelling accuracy of 30.8%, 26.3% and 31% for the three OAM modes. Moreover, the receiver sensitivity of the proposed E2E learning strategy is higher than for the CGAN emulator by 3, 2.5, 2.2 dBm and the real channel by 5.5, 5.1, and 5.3 dBm for the three OAM modes, respectively. Our experimental results demonstrate that the proposed FDFDnet emulator-based E2E learning strategy is a promising contender for achieving ultra-high-capacity interconnectivity between data centers.