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Background: Non-invasive imaging methods are still lacking for evaluating bone changes in chronic kidney diseases (CKD). Purpose: To investigate the feasibility of chest CT radiomics in evaluating bone changes caused by CKD. Material and Methods: In total, 75 patients with stage 1 CKD (CKD1) and 75 with stage 5 CKD (CKD5) were assessed using the chest CT radiomics method. Radiomics features of bone were obtained using 3D Slicer software and were then compared between CKD1 and CKD5 cases. The methods of maximum correlation minimum redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) were used to establish a prediction model to determine CKD. The receiver operating characteristic (ROC) curve was used to determine the performance of the model. Results: Cases of CKD1 and CKD5 differed in 40 radiomics features (P <0.05). Using the mRMR and LASSO methods, five features were finally selected to establish a predication model. The area under the receiver operating characteristic curve of the model in the determination of CKD1 and CKD5 was 0.903 and 0.854, respectively, for the training and validation cohorts. Conclusion: Chest CT radiomics is feasible in evaluating bone changes caused by CKD. [ABSTRACT FROM AUTHOR]

• Bionic sensor that responds to underwater strain, breathing, bubbles. • Superhydrophobic sensor for detecting humidity. • Underwater bubble response with good robustness. • Applications for real-time monitoring of the underwater physiological signals. The development of multifunctional flexible sensors capable of monitoring different physiological signals of the body underwater holds great practical significance in safeguarding the well-being of divers during their subaquatic activities. Here, we prepared a multilayer multifunctional sensor that mimics the structure of human skin by sequentially constructing a sensing layer formed by multi-walled carbon nanotubes and a hydrophobic protective layer formed by organosilicon dioxide (o-SiO 2) on the elastomer surface. The o-SiO 2 layer is superhydrophobic and breathable, also allowing the sensing layer to be only partially wetted. The sensor can monitor human respiration by sensing humidity due to breathability of protective layer. Additionally, the superhydrophobic surface ensures stable strain monitoring even underwater. The partially wetted sensing layer allows the sensor to respond to its immersion and surfacing processes, as well as underwater bubbles. These multifunctional sensors are capable of real-time monitoring of divers' physiological signals, including breathing patterns and motions, throughout underwater activities. [ABSTRACT FROM AUTHOR]

Background: Carcass traits are essential economic traits in the commercial pig industry. However, the genetic mechanism of carcass traits is still unclear. In this study, we performed a genome-wide association study (GWAS) based on the specific-locus amplified fragment sequencing (SLAF-seq) to study seven carcass traits on 223 four-way intercross pigs, including dressing percentage (DP), number of ribs (RIB), skin thinkness (ST), carcass straight length (CSL), carcass diagonal length (CDL), loin eye width (LEW), and loin eye thickness (LET). Results: A total of 227,921 high-quality single nucleotide polymorphisms (SNPs) were detected to perform GWAS. A total of 30 SNPs were identified for seven carcass traits using the mixed linear model (MLM) (p < 1.0 × 10− 5), of which 9 SNPs were located in previously reported quantitative trait loci (QTL) regions. The phenotypic variation explained (PVE) by the significant SNPs was from 2.43 to 16.32%. Furthermore, 11 candidate genes (LYPLAL1, EPC1, MATN2, ZFAT, ZBTB10, ZNF704, INHBA, SMYD3, PAK1, SPTBN2, and ACTN3) were found for carcass traits in pigs. Conclusions: The GWAS results will improve our understanding of the genetic basis of carcass traits. We hypothesized that the candidate genes associated with these discovered SNPs would offer a biological basis for enhancing the carcass quality of pigs in swine breeding. [ABSTRACT FROM AUTHOR]

Despite some progress in pneumococcal immunization, the global burden of pneumococcal infection remains high, and pneumococcal disease remains a public health concern. Studies in China and abroad have found that 23-valent pneumococcal polysaccharide vaccine (PPV23) vaccination can effectively prevent invasive pneumococcal disease. This phase Ⅰ clinical study assessed the safety and immunogenicity of a PPV23 vaccine candidate. All subjects were randomly assigned to receive one dose intramuscular injection of experimental vaccine or control vaccine at a ratio of 1:1. The incidence of any adverse events was observed within 30 min, 0–7 days and 8–28 days post vaccination and the incidence of abnormal blood biochemical and blood routine indicators were tested on the 4th day post vaccination, the incidence of serious adverse events (SAEs) at 6 months post vaccination was recorded. Blood samples were collected prior to vaccination and on the 28th day post vaccination, and serum antibodies were detected by enzyme linked immunosorbent assay (ELISA). The most common adverse reaction was pain at the injection site, followed by erythema. There was no significant difference of the incidence of systemic adverse reactions between the two vaccine groups. The adverse reactions observed in the trial were all common vaccination-related reactions, and no serious adverse reactions were observed. Compared to pre-vaccination, the (geometric mean concentrations) GMCs of IgG (immunoglobulin G) specific antibody against each serotype were all increased in the experimental group and the control group, there were statistical differences in seroconversion rates of serotypes 4 and 20 between the two vaccine groups. This clinical study showed good safety of the PPV23 vaccine candidate produced by Ab&b Biotechnology Co., Ltd.JS had good safety after vaccination in people aged 2 years and older. At the same time, good immunogenicity was also demonstrated. [ABSTRACT FROM AUTHOR]

Background: As biomarkers, microRNAs (miRNAs) are closely associated with the occurrence, progression, and prognosis of non-small cell lung cancer (NSCLC). However, the prognostic predictive value of miRNAs in NSCLC has rarely been explored. In this study, the value in prognosis prediction of NSCLC was mined based on data mining models using clinical data and plasma miRNAs biomarkers. Methods: A total of 69 patients were included in this prospective cohort study. After informed consent, they filled out questionnaires and had their peripheral blood collected. The expressions of plasma miRNAs were examined by quantitative polymerase chain reaction (qPCR). The Whitney U test was used to analyze non-normally distributed data. Kaplan-Meier was used to plot the survival curve, the log-rank test was used to compare with the overall survival curve, and the Cox proportional hazards model was used to screen the factors related to the prognosis of lung cancer. Data mining techniques were utilized to predict the prognostic status of patients. Results: We identified that smoking (HR = 2.406, 95% CI = 1.256–4.611), clinical stage III + IV (HR = 5.389, 95% CI = 2.290-12.684), the high expression group of miR-20a (HR = 4.420, 95% CI = 1.760–11.100), the high expression group of miR-197 (HR = 3.828, 95% CI = 1.778–8.245), the low expression group of miR-145 (HR = 0.286, 95% CI = 0.116–0.709), and the low expression group of miR-30a (HR = 0.307, 95% CI = 0.133–0.706) was associated with worse prognosis. Among the five data mining models, the decision trees (DT) C5.0 model performs the best, with accuracy and Area Under Curve (AUC) of 93.75% and 0.929 (0.685, 0.997), respectively. Conclusion: The results showed that the high expression level of miR-20a and miR-197, the low expression level of miR-145 and miR-30a were strongly associated with poorer prognosis in NSCLC patients, and the DT C5.0 model may serve as a novel, accurate, method for predicting prognosis of NSCLC. [ABSTRACT FROM AUTHOR]

• Genetically predicted rheumatoid arthritis was associated with increased frailty index and Fried frailty score. • Neither genetically predicted frailty index nor Fried frailty score showed any association with the risk of rheumatoid arthritis. • Inflammatory cytokines were involved in the mechanism of rheumatoid arthritis-induced frailty. Previous observational studies have suggested the association between rheumatoid arthritis (RA) and frailty. However, it remains obscure whether this association is causal. This study aims to investigate the causal association of RA with frailty and the mediation effect of inflammatory cytokines using Mendelian randomization (MR) design. Summary-level data for RA (N = 58,284), frailty index (FI) (N = 175,226), Fried frailty score (FFS) (N = 386,565), and 41 inflammatory cytokines (N = 8,293) were obtained from recent genome-wide association studies. Univariable and multivariable MR analyses were conducted to investigate and verify the causal association of RA with frailty. The potential mediation effects of inflammatory cytokines were estimated using two-step MR. Univariable inverse variance weighted MR analysis suggested that genetically determined RA was associated with increased FI (beta=0.021; 95 % CI: 0.012, 0.03; p = 2.2 × 10−6) and FFS (beta=0.011; 95 %CI: 0.007, 0.015; p = 8.811 × 10−8). The consistent results were observed in multivariable MR analysis after adjustment for asthma, smoking, BMI, physical activity, telomere length, and depression. Mediation analysis showed evidence of an indirect effect of RA on FI through monokine induced by interferon-gamma (MIG) with a mediated proportion of 9.8 % (95 %CI: 4.76 %, 19.05 %), on FFS via MIG and stromal cell-derived factor-1 alpha with a mediated proportion of 9.6 % (95 %CI: 0 %, 18.18 %) and 8.44 % (95 %CI: 0 %, 18.18 %), respectively. This study provided credible evidence that genetically predicted RA was associated with a higher risk of frailty. Additionally, inflammatory cytokines were involved in the mechanism of RA-induced frailty. [ABSTRACT FROM AUTHOR]

[Display omitted] • Mini-KF-SLE-ISD was developed for aldehyde sample preparation in edible oil. • Simultaneous derivatization and extraction of aldehydes in edible oils were achieved. • Box-Behnken design optimization resulted in enhanced detection sensitivity. • The method proved simple, cost-effective, highly sensitive, and easy to automate. • Aldehyde changes during heating exhibited distinctions among various oil types. Heating edible oils generates aldehydes, potentially leading to adverse health effects, making their analysis essential for quality control. This study presents a convenient miniaturized kapok fiber-supported liquid-phase extraction/ in-situ derivatization method for the simultaneous extraction and derivatization of aldehydes in oils. The method involves placing 150 mg oil into a 1 mL pipette tip packed with 25 mg kapok fiber, adding 150 μL ACN with 1.5 mg mL−1 DNPH, and post 30-minute static extraction, retrieving the extractant with a pipettor for liquid chromatography-tandem mass spectrometry analysis. By optimizing critical parameters through a Box-Behnken design, the method exhibits good linearity (1–500 ng g−1, R2 ≥ 0.991), low detection limits (0.2–1.0 ng g−1), excellent accuracy (95.3–107.1%) and high precisions (relative standard deviation < 7.9%). This method simplifies sample preparation processes, cuts solvent use, and facilitates automation. It effectively identifies ten aldehyde variations in six heated oils, displaying distinct profiles consistent with prior research. [ABSTRACT FROM AUTHOR]

Therapeutic drug monitoring (TDM) of antidepressants is essential for monitoring patient medication to avoid drug toxicity, complications, or nonadherence. Chromatographic techniques with high sensitivity and reproducibility are the main detection method for antidepressants. Effective pretreatment of biological sample processes is necessary prior to instrumental analysis. Magnetic solid-phase extraction (MSPE) has received much attention for its advantages of simple operation, rapidity, cost-effectiveness and low organic solvent consumption. Therefore, the development of a suitable and green magnetic sorbent for the detection of antidepressants in plasma and urine is apparently necessary. (88) A magnetic phytic acid-modified kapok fiber biochar sorbent (Fe 3 O 4 /PAKFBC) was successfully synthesized by pyrolytic impregnation and physical milling methods. Fe 3 O 4 /PAKFBC exhibited a large specific surface area (214 m2 g−1) and a rich pore structure (5–10 nm). The extraction equilibrium, using 10 mg Fe 3 O 4 /PAKFBC, can be completed in about 1 min. The density functional theory (DFT) results showed that the adsorption mechanism of Fe 3 O 4 /PAKFBC on the six antidepressants mainly included electrostatic interactions, van der Waals interactions, π-π interactions and weak hydrogen bonding. Examination using the greenness assessment tools showed that the developed method exhibited excellent greenness. By combining with liquid chromatography-ultraviolet (LC-UV), a quantitative method with good linearity (R2 > 0.993) and relative recoveries (92.4–107.7%) and negligible matrix effect (−11.5–6.0%) was developed. The Fe 3 O 4 /PAKFBC successfully detected six antidepressants in plasma and urine samples, requiring no pH adjustment with buffer salts. (142) The environmental sustainability of the proposed methods was affirmed by six greenness evaluation tools, all indicating exceptional eco-friendliness. The Fe 3 O 4 /PAKFBC demonstrated outstanding greenness in both its creation and analytical application, proving highly effective in real sample applications and showcasing potential for broader use. This study contributes to a deeper and broader understanding of the microscopic adsorption mechanism, which can help in the optimization and development of more green sorbents. (69). • Preparation of Fe 3 O 4 /PAKFBC sorbent without the use of toxic solvents. • Fe 3 O 4 /PAKFBC has a large specific surface area (214 m2/g) and rich pore structure. • PA impregnation increases hydrophilicity and dispersion of KFBC. • DFT reveal the adsorption mechanism of Fe 3 O 4 /PAKFBC with six antidepressants. • The method with excellent greenness in sorbent preparation and sample analysis. [ABSTRACT FROM AUTHOR]

The addition of synthetic phenolic antioxidants can effectively delay or prevent oxidation of edible oils. However, excessive use of these antioxidants can have negative impacts, which emphasizes the importance of accurate analysis methods to determine their presence in edible oils. Given the large number of food samples involved in regulatory purposes, there is a need to develop high-throughput and cost-effective detection methods for routine analysis. However, the existing methods are not suitable, indicating a need for further improvement. This study presents a technique that combines miniaturized-kapok fiber-supported liquid-phase extraction (mini-KF-SLE) with gas chromatography-flame ionization detection (GC-FID) to determine synthetic antioxidants like 3- tert -butyl-4-hydroxyanisole, 3,5-di- tert -butyl-4-hydroxytoluene, and tert -butylhydroquinone in edible oils. The mini-KF-SLE device consists of 20 mg of kapok fibers placed in a 1 mL pipette tip attached to a pipette. The extraction procedure involves three simple steps: loading the oil sample (150 mg), adding the extractant (150 µL of ACN), and eluting the extractant by applying air pressure using a pipette. The developed mini-KF-SLE-GC-FID method shows satisfactory quantitation ability (R2 >0.99) and detection limits of 0.4–0.5 µg/g. Moreover, the relative standard deviations for all analytes were below 9.2%, indicating good precise of the method for routine analysis. The proposed method also exhibits excellent environmental friendliness, as evidenced by three widely recognized metrics. Overall, the mini-KF-SLE-GC-FID method provides a convenient, low-cost, environmentally friendly, and easy to automate alternative for routinely determining synthetic antioxidants in edible oils. • Mini-KF-SLE was combined with GC for analyzing synthetic antioxidants in oils. • Extraction involves a simple three-step protocol using a pipette. • The method consumes only 150 mg of edible oil sample and 150 µL of ACN. • Three metrics of AES, GAPI, and AGREE demonstrates excellent greenness. • The method is low-cost and easy to automate, suitable for routine analysis. [ABSTRACT FROM AUTHOR]