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.

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.

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.

Cyclo(L-Pro-L-Trp) from Chilobrachys jingzhao alleviates formalin-induced inflammatory pain by suppressing the inflammatory response and inhibiting TRAF6-mediated MAPK and NF-κB signaling pathways.

Chronic pain has emerged as a significant public health issue, seriously affecting patients' quality of life and psychological well-being, with a lack of effective pharmacological treatments. Numerous studies have indicated that macrophages play a crucial role in inflammatory pain, and targeting neuro-immune interactions for drug development may represent a promising direction for pain management. Chilobrachys jingzhao (C. jingzhao) is used as a folk medicine of the Li nationality with the efficacy of eliminating swelling, detoxicating, and relieving pain, and the related products are widely used in the market. However, the chemical constituents of C. jingzhao have not been reported, and the pharmacodynamic substance and the precise functional mechanism are unrevealed. Here we isolated a cyclic dipeptide, cyclo(L-Pro-L-Trp) (CPT) from C. jingzhao for the first time. CPT remarkably alleviated formalin-induced inflammatory pain and significantly inhibited inflammatory responses. In vivo, CPT attenuated neutrophil infiltration and plantar tissue edema and suppressed the mRNA expression of pro-inflammatory molecules. In vitro, CPT suppressed inflammation triggered by lipopolysaccharide (LPS) in both RAW 264.7 and iBMDM cells, reducing expressions of inducible nitric oxide synthase (iNOS), superoxide, and pro-inflammatory molecules. A mechanistic study revealed that CPT exerted an anti-inflammatory activity by blocking the mitogen-activated protein kinases (MAPK) and nuclear factor-kappa B (NF-κB) signaling pathways, as well as alleviating the ubiquitination of tumor necrosis factor receptor-associated factor 6 (TRAF6). Our results elucidated the pharmacodynamic material basis of C. jingzhao, and CPT can be a promising lead for alleviating inflammation and inflammatory pain.

Biomechanical analysis of an absorbable material for treating fractures of the inferior orbital wall.

AIM: To investigate the biomechanical properties and practical application of absorbable materials in orbital fracture repair. METHODS: The three-dimensional (3D) model of orbital blowout fractures was reconstructed using Mimics21.0 software. The repair guide plate model for inferior orbital wall fracture was designed using 3-matic13.0 and Geomagic wrap 21.0 software. The finite element model of orbital blowout fracture and absorbable repair plate was established using 3-matic13.0 and ANSYS Workbench 21.0 software. The mechanical response of absorbable plates, with thicknesses of 0.6 and 1.2 mm, was modeled after their placement in the orbit. Two patients with inferior orbital wall fractures volunteered to receive single-layer and double-layer absorbable plates combined with 3D printing technology to facilitate surgical treatment of orbital wall fractures. RESULTS: The finite element models of orbital blowout fracture and absorbable plate were successfully established. Finite element analysis (FEA) showed that when the Young's modulus of the absorbable plate decreases to 3.15 MPa, the repair material with a thickness of 0.6 mm was influenced by the gravitational forces of the orbital contents, resulting in a maximum total deformation of approximately 3.3 mm. Conversely, when the absorbable plate was 1.2 mm thick, the overall maximum total deformation was around 0.4 mm. The half-year follow-up results of the clinical cases confirmed that the absorbable plate with a thickness of 1.2 mm had smaller maximum total deformation and better clinical efficacy. CONCLUSION: The biomechanical analysis observations in this study are largely consistent with the clinical situation. The use of double-layer absorbable plates in conjunction with 3D printing technology is recommended to support surgical treatment of infraorbital wall blowout fractures.

The structural basis of the activation and inhibition of DSR2 NADase by phage proteins.

DSR2, a Sir2 domain-containing protein, protects bacteria from phage infection by hydrolyzing NAD+. The enzymatic activity of DSR2 is triggered by the SPR phage tail tube protein (TTP), while suppressed by the SPbeta phage-encoded DSAD1 protein, enabling phages to evade the host defense. However, the molecular mechanisms of activation and inhibition of DSR2 remain elusive. Here, we report the cryo-EM structures of apo DSR2, DSR2-TTP-NAD+ and DSR2-DSAD1 complexes. DSR2 assembles into a head-to-head tetramer mediated by its Sir2 domain. The C-terminal helical regions of DSR2 constitute four partner-binding cavities with opened and closed conformation. Two TTP molecules bind to two of the four C-terminal cavities, inducing conformational change of Sir2 domain to activate DSR2. Furthermore, DSAD1 competes with the activator for binding to the C-terminal cavity of DSR2, effectively suppressing its enzymatic activity. Our results provide the mechanistic insights into the DSR2-mediated anti-phage defense system and DSAD1-dependent phage immune evasion.

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.

Association between serum neurofilament light chains (sNfL) and neurologic disorders in a representative sample of US adults: a cross-sectional study.

BACKGROUND: While increased neurofilament light chain (NfL) in serum concentrations are linked to the progression of several neurological conditions, their distribution and implications within the general adult population remain largely unexplored. The current research aims to clarify the relationship between serum NfL levels and neurological disorders in a broad and representative population sample. METHODS: We utilized information gathered from 1751 adults involved in the 2013-2014 cycle of the National Health and Nutrition Examination Survey . Our analytical approach encompassed logistic regression, smoothed curve fitting, and subgroup analyses to identify potential correlations between serum NfL levels and neurological conditions, such as depression, severe hearing and visual impairments, stroke, subjective memory deficits, and sleep problems. RESULTS: After adjusting for all confounders, we found that higher serum NfL levels were significantly associated with increased risks of depression, stroke, subjective memory deficits, and longer sleep duration (p < 0.05). Subgroup analyses supported these findings. Additionally, BMI significantly influenced the relationship between serum NfL levels and long-term subjective memory decline. CONCLUSION: Our research shows that higher serum NfL levels are strongly related to an elevated risk for several neurological disorders. These findings highlight the role of serum NfL serving as a critical marker for early detection and monitoring of neurological conditions, emphasizing its importance in both clinical and public health settings.

Differentially expressed heterogeneous overdispersion genes testing for count data.

The mRNA-seq data analysis is a powerful technology for inferring information from biological systems of interest. Specifically, the sequenced RNA fragments are aligned with genomic reference sequences, and we count the number of sequence fragments corresponding to each gene for each condition. A gene is identified as differentially expressed (DE) if the difference in its count numbers between conditions is statistically significant. Several statistical analysis methods have been developed to detect DE genes based on RNA-seq data. However, the existing methods could suffer decreasing power to identify DE genes arising from overdispersion and limited sample size, where overdispersion refers to the empirical phenomenon that the variance of read counts is larger than the mean of read counts. We propose a new differential expression analysis procedure: heterogeneous overdispersion genes testing (DEHOGT) based on heterogeneous overdispersion modeling and a post-hoc inference procedure. DEHOGT integrates sample information from all conditions and provides a more flexible and adaptive overdispersion modeling for the RNA-seq read count. DEHOGT adopts a gene-wise estimation scheme to enhance the detection power of differentially expressed genes when the number of replicates is limited as long as the number of conditions is large. DEHOGT is tested on the synthetic RNA-seq read count data and outperforms two popular existing methods, DESeq2 and EdgeR, in detecting DE genes. We apply the proposed method to a test dataset using RNAseq data from microglial cells. DEHOGT tends to detect more differently expressed genes potentially related to microglial cells under different stress hormones treatments.

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.

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.

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.

Mapping Single-Cell Transcriptomes of Endometrium Reveals Potential Biomarkers in Endometrial Cancer.

Background: The heterogeneity and dynamic changes of endometrial cells have a significant impact on health as they determine the normal function of the endometrium during the menstrual cycle. Dysfunction of the endometrium can lead to the occurrence of various gynecological diseases. Therefore, deconvolution of immune microenvironment that drives transcriptional programs throughout the menstrual cycle is key to understand regulatory biology of endometrium. Methods: Herein, we comprehensively analyzed single-cell transcriptome of 59,397 cells across ten human endometrium samples and revealed the dynamic cellular heterogeneity throughout the menstrual cycle. Results: We identified two perivascular cell subtypes, four epithelial subtypes and four fibroblast cell types in endometrium. Moreover, we inferred the cell type-specific transcription factor (TF) activities and linked critical TFs to transcriptional output of diverse immune cell types, highlighting the importance of transcriptional regulation in endometrium. Dynamic interactions between various types of cells in endometrium contribute to a range of biological pathways regulating differentiation of secretory. Integration of the molecular biomarkers identified in endometrium and bulk transcriptome of 535 endometrial cancers (EC), we revealed five RNA-based molecular subtypes of EC with highly intratumoral heterogeneity and different clinical manifestations. Mechanism analysis uncovered clinically relevant pathways for pathogenesis of EC. Conclusion: In summary, our results revealed the dynamic immune microenvironment of endometrium and provided novel insights into future development of RNA-based treatments for endometriosis and endometrial carcinoma.

Roles of AMPA receptors in social behaviors.

As a crucial player in excitatory synaptic transmission, AMPA receptors (AMPARs) contribute to the formation, regulation, and expression of social behaviors. AMPAR modifications have been associated with naturalistic social behaviors, such as aggression, sociability, and social memory, but are also noted in brain diseases featuring impaired social behavior. Understanding the role of AMPARs in social behaviors is timely to reveal therapeutic targets for treating social impairment in disorders, such as autism spectrum disorder and schizophrenia. In this review, we will discuss the contribution of the molecular composition, function, and plasticity of AMPARs to social behaviors. The impact of targeting AMPARs in treating brain disorders will also be discussed.

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.

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.

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.

Predicting vulnerable carotid plaques by detecting wall shear stress based on ultrasonic vector flow imaging.

OBJECTIVE: Carotid plaque vulnerability is a significant factor in the risk of cardiocerebrovascular events, with intraplaque neovascularization (IPN) being a crucial characteristic of plaque vulnerability. This study investigates the value of ultrasound vector flow imaging (V-flow) for measuring carotid plaque wall shear stress (WSS) in predicting the extent of IPN. METHODS: We enrolled 140 patients into three groups: 53 in the plaque group (72 plaques), 23 in the stenosis group (27 plaques), and 64 in the control group. V-flow was used to measure WSS parameters, including the average WSS (WSS mean) and the maximum WSS (WSS max), across three plaque locations: mid-upstream, maximum thickness, and mid-downstream. Contrast-enhanced ultrasound examination was used in 76 patients to analyze IPN and its correlation with WSS parameters. RESULTS: WSS max in the stenosis group was significantly higher than that in the control and plaque groups at the maximum thickness part (P < .05) and WSS mean in the stenosis group was significantly lower than that in the control group at the mid-upstream and mid-downstream segments (P < .05). WSS mean in the plaque group was significantly lower than that of the control group at all three locations (P < .05). Contrast-enhanced ultrasound examination revealed that plaques with neovascularization enhancement exhibited significantly higher WSS values (P < .05), with a positive correlation between WSS parameters and IPN enhancement grades, particularly WSS max at the thickest part (r = 0.508). Receiver operating characteristic curve analysis of WSS parameters for evaluating IPN showed that the efficacy of WSS max in evaluating IPN was better than that of WSS mean (P < .05), with an area under the curve of 0.7762 and 0.6973 (95% confidence intervals, 0.725-0.822 and 0.642-0.749, respectively). The cut-offs were 4.57 Pa and 1.12 Pa, sensitivities were 74.03% and 63.64%, and specificities were 75.00% and 68.18%. CONCLUSIONS: V-flow effectively measures WSS in carotid plaques. WSS max provides a promising metric for assessing IPN, offering potential insights into plaque characteristics and showing some potential in predicting plaque vulnerability.