Life-course obesity and heart failure: a two-sample Mendelian randomization study.

Heart failure is a multifaceted clinical syndrome, with obesity identified as a significant modifiable risk factor. This study employed a two-sample Mendelian randomization (MR) design, incorporating obesity data across life stages, to elucidate the causal link between obesity and heart failure. Data on heart failure from the 2023 Finngen database and genetic predictors of obesity from the IEU OpenGWAS project were analyzed using the IVW method, MR-Egger regression, weighted median, simple mode, weighted mode, and scatter plots. Heterogeneity was assessed with Cochran's Q test, and horizontal pleiotropy with MR-Egger intercept test. Sensitivity to single-nucleotide polymorphisms (SNPs) was tested via leave-one-out analysis, and funnel plots were utilized for visual inspection of horizontal pleiotropy. Statistical powers were also calculated. The MR analysis findings indicate a significant relationship between birth weight and the likelihood of developing heart failure (Odds Ratio [OR] 1.134, 95% Confidence Interval [CI] 1.033-1.245, P = 0.008). In addition, a heightened childhood BMI was found to be a significant predictor of heart failure risk (OR 1.307, 95% CI 1.144-1.494, P = 8.51E-05), as was childhood obesity (OR 1.123, 95% CI 1.074-1.173, P = 2.37E-07). Furthermore, adult BMI sex-combined exhibited a strong correlation with the risk of heart failure (OR 2.365, 95% CI 2.128-2.629, P = 1.91E-57). Sensitivity analyses provided further support for the reliability of these results, with no significant indication of horizontal pleiotropy observed. This study shows that obesity, including childhood obesity, is linked to a higher risk of heart failure. These findings highlight the urgent need for early weight management interventions in public health and clinical settings to reduce heart failure rates.

Construction and evaluation of a mortality prediction model for patients with acute kidney injury undergoing continuous renal replacement therapy based on machine learning algorithms.

BACKGROUND: To construct and evaluate a predictive model for in-hospital mortality among critically ill patients with acute kidney injury (AKI) undergoing continuous renal replacement therapy (CRRT), based on nine machine learning (ML) algorithm. METHODS: The study retrospectively included patients with AKI who underwent CRRT during their initial hospitalization in the United States using the medical information mart for intensive care (MIMIC) database IV (version 2.0), as well as in the intensive care unit (ICU) of Huzhou Central Hospital. Patients from the MIMIC database were used as the training cohort to construct the models (from 2008 to 2019, n = 1068). Patients from Huzhou Central Hospital were utilized as the external validation cohort to evaluate the models (from June 2019 to December 2022, n = 327). In the training cohort, least absolute shrinkage and selection operator (LASSO) regression with cross-validation was employed to select features for constructing the model and subsequently established nine ML predictive models. The performance of these nine models on the external validation cohort dataset was comprehensively evaluated based on the area under the receiver operating characteristic curve (AUROC) and the optimal model was selected. A static nomogram and a web-based dynamic nomogram were presented, with a comprehensive evaluation from the perspectives of discrimination (AUROC), calibration (calibration curve) and clinical practicability (DCA curves). RESULTS: Finally, 1395 eligible patients were enrolled, including 1068 patients in the training cohort and 327 patients in the external validation cohort. In the training cohort, LASSO regression with cross-validation was employed to select features and nine models were individually constructed. Compared to the other eight models, the Lasso regularized logistic regression (Lasso-LR) model exhibited the highest AUROC (0.756) and the optimal calibration curve. The DCA curve suggested a certain clinical utility in predicting in-hospital mortality among critically ill patients with AKI undergoing CRRT. Consequently, the Lasso-LR model was the optimal model and it was visualized as a common nomogram (static nomogram) and a web-based dynamic nomogram (https://chsyh2006.shinyapps.io/dynnomapp/). Discrimination, calibration and DCA curves were employed to assess the performance of the nomogram. The AUROC for the training and external validation cohorts in the nomogram model was 0.771 (95%CI: 0.743, 0.799) and 0.756 (95%CI: 0.702, 0.809), respectively. The calibration slope and Brier score for the training cohort were 1.000 and 0.195, while for the external validation cohort, they were 0.849 and 0.197, respectively. The DCA indicated that the model had a certain clinical application value. CONCLUSIONS: Our study selected the optimal model and visualized it as a static and dynamic nomogram integrating clinical predictors, so that clinicians can personalized predict the in-hospital outcome of critically ill patients with AKI undergoing CRRT upon ICU admission.

Characterization and stability of lycopene-loaded high internal phase emulsion stabilized by ovalbumin-chitosan complexes.

Lycopene, a carotenoid with numerous physiological benefits, particularly in its Z-isomer form, faces challenges in its application due to low chemical stability. To address this limitation, high internal phase emulsion was successfully synthesized using ovalbumin-chitosan complexes. The aim was to enhance the stability of lycopene including Z-lycopene. The solubility, particle size, ζ-potential and uniformity of the mixture were dependent on pH value and biopolymer proportion. Notably, optimal ovalbumin-chitosan complex formation occurred at pH 2.5 with a ratio of 4:1 resulting in the highest solubility and optimal uniformity which contributed to its superior emulsification properties. Evaluation of encapsulating efficiency and loading amount revealed 98.19% and 1.7661 mg/g respectively for lycopene in ovalbumin-chitosan stabilized emulsions, inhibiting the transformation from Z-lycopene to (all-E)-lycopene. The encapsulated lycopene possessed UV stability where retention rate remained high at 81.86%. The retention rate was up to 65.37% and 41.82% at 45 °C and 80 °C, respectively.

Non-Abelian Holonomy in Degenerate Non-Hermitian Systems.

Non-Abelian holonomy, a noncommutative process that measures the parallel transport of non-Abelian gauge fields, has so far been realized in degenerate Hermitian systems with degenerate eigenstates or nondegenerate non-Hermitian systems with exceptional points. Here, we introduce non-Abelian holonomy into degenerate non-Hermitian systems possessing degenerate exceptional points and degenerate energy topologies. The interplay between energy degeneracy and energy topology around exceptional points leads to a non-Abelian holonomy with multiple energy levels and multiple degenerate levels simultaneously, going beyond that in degenerate Hermitian systems with a single energy level, or in nondegenerate non-Hermitian systems with a single degenerate level. We exploit an on-chip photonic platform to experimentally demonstrate the holonomy induced non-Abelian phenomenon, including the switching of eigenstates associated with different degenerate exceptional points and sequence-dependent holonomic outcomes. Our work shifts the paradigm of non-Abelian holonomy and adds new degrees of freedom for non-Abelian applications.

Periodic protein-restricted diets extend the lifespan of high-fat diet-induced Drosophila melanogaster males.

Research has shown that sustained protein restriction can improve the effects of a high-fat diet on health and extend lifespan. However, long-term adherence to a protein-restricted diet is challenging. Therefore, we used a fly model to investigate whether periodic protein restriction (PPR) could also mitigate the potential adverse effects of a high-fat diet and extend healthy lifespan. Our study results showed that PPR reduced body weight, lipid levels, and oxidative stress induced by a high-fat diet in flies and significantly extended the healthy lifespan of male flies. Lipid metabolism and transcriptome results revealed that the common differences between the PPR group and the control group and high-fat group showed a significant decrease in palmitic acid in the PPR group; the enriched common differential pathways Toll and Imd were significantly inhibited in the PPR group. Further analysis indicated a significant positive correlation between palmitic acid levels and gene expression in the Toll and Imd pathways. This suggests that PPR effectively improves fruit fly lipid metabolism, reduces palmitic acid levels, and thereby suppresses the Toll and Imd pathways to extend the healthy lifespan of flies. Our study provides a theoretical basis for the long-term effects of PPR on health and offers a new dietary adjustment option for maintaining health in the long term.

Risk prediction models for successful discontinuation in acute kidney injury undergoing continuous renal replacement therapy.

Continuous renal replacement therapy (CRRT) is a commonly utilized treatment modality for individuals experiencing severe acute kidney injury (AKI). The objective of this research was to construct and assess prognostic models for the timely discontinuation of CRRT in critically ill AKI patients receiving this intervention. Data were collected retrospectively from the MIMIC-IV database (n = 758) for model development and from the intensive care unit (ICU) of Huzhou Central Hospital (n = 320) for model validation. Nine machine learning models were developed by utilizing LASSO regression to select features. In the training set, all models demonstrated an AUROC exceeding 0.75. In the validation set, the XGBoost model exhibited the highest AUROC of 0.798, leading to its selection as the optimal model for the development of an online calculator for clinical applications. The XGBoost model demonstrates significant predictive capabilities in determining the discontinuation of CRRT.

Association between lactate/albumin ratio and prognosis in critically ill patients with acute kidney injury undergoing continuous renal replacement therapy.

BACKGROUND: The primary objective was to examine the association between the lactate/albumin ratio (LAR) and the prognosis of patients with acute kidney injury (AKI) undergoing continuous renal replacement therapy (CRRT). METHODS: Utilizing the Medical Information Mart for Intensive Care IV (MIMIC-IV, v2.0) database, we categorized 703 adult AKI patients undergoing CRRT into survival and non-survival groups based on 28-day mortality. Patients were further grouped by LAR tertiles: low (< 0.692), moderate (0.692-1.641), and high (> 1.641). Restricted cubic splines (RCS), Least Absolute Shrinkage and Selection Operator (LASSO) regression, inverse probability treatment weighting (IPTW), and Kaplan-Meier curves were employed. RESULTS: In our study, the patients had a mortality rate of 50.07% within 28 days and 62.87% within 360 days. RCS analysis revealed a non-linear correlation between LAR and the risk of mortality at both 28 and 360 days. Cox regression analysis, which was adjusted for nine variables identified by LASSO, confirmed that a high LAR (>1.641) served as an independent predictor of mortality at these specific time points (p < 0.05) in AKI patients who were receiving CRRT. These findings remained consistent even after IPTW adjustment, thereby ensuring a reliable and robust outcome. Kaplan-Meier survival curves exhibited a gradual decline in cumulative survival rates at both 28 and 360 days as the LAR values increased (log-rank test, χ2 = 48.630, p < 0.001; χ2 = 33.530, p < 0.001). CONCLUSION: A high LAR (>1.641) was found to be an autonomous predictor of mortality at both 28 and 360 days in critically ill patients with AKI undergoing CRRT.

Weed detection and recognition in complex wheat fields based on an improved YOLOv7.

Introduction: The precise detection of weeds in the field is the premise of implementing weed management. However, the similar color, morphology, and occlusion between wheat and weeds pose a challenge to the detection of weeds. In this study, a CSCW-YOLOv7 based on an improved YOLOv7 architecture was proposed to identify five types of weeds in complex wheat fields. Methods: First, a dataset was constructed for five weeds that are commonly found, namely, Descurainia sophia, thistle, golden saxifrage, shepherd's purse herb, and Artemisia argyi. Second, a wheat weed detection model called CSCW-YOLOv7 was proposed to achieve the accurate identification and classification of wheat weeds. In the CSCW-YOLOv7, the CARAFE operator was introduced as an up-sampling algorithm to improve the recognition of small targets. Then, the Squeeze-and-Excitation (SE) network was added to the Extended Latent Attention Networks (ELAN) module in the backbone network and the concatenation layer in the feature fusion module to enhance important weed features and suppress irrelevant features. In addition, the contextual transformer (CoT) module, a transformer-based architectural design, was used to capture global information and enhance self-attention by mining contextual information between neighboring keys. Finally, the Wise Intersection over Union (WIoU) loss function introducing a dynamic nonmonotonic focusing mechanism was employed to better predict the bounding boxes of the occluded weed. Results and discussion: The ablation experiment results showed that the CSCW-YOLOv7 achieved the best performance among the other models. The accuracy, recall, and mean average precision (mAP) values of the CSCW-YOLOv7 were 97.7%, 98%, and 94.4%, respectively. Compared with the baseline YOLOv7, the improved CSCW-YOLOv7 obtained precision, recall, and mAP increases of 1.8%, 1%, and 2.1%, respectively. Meanwhile, the parameters were compressed by 10.7% with a 3.8-MB reduction, resulting in a 10% decrease in floating-point operations per second (FLOPs). The Gradient-weighted Class Activation Mapping (Grad-CAM) visualization method suggested that the CSCW-YOLOv7 can learn a more representative set of features that can help better locate the weeds of different scales in complex field environments. In addition, the performance of the CSCW-YOLOv7 was compared to the widely used deep learning models, and results indicated that the CSCW-YOLOv7 exhibits a better ability to distinguish the overlapped weeds and small-scale weeds. The overall results suggest that the CSCW-YOLOv7 is a promising tool for the detection of weeds and has great potential for field applications.

Metabolic syndrome and risk of subclinical hypothyroidism: a systematic review and meta-analysis.

Background: Subclinical hypothyroidism (SCH) is a common endocrine subclinical disorder, the main adverse consequences of which are the development of clinical hypothyroidism and the promotion of ischemic heart disease. Metabolic syndrome (MetS) is a collection of metabolic problems. The goal of this meta-analysis was to evaluate the relationship between MetS and SCH. Methods: Suitable publications were identified using PubMed, Embase, and the Cochrane Library. The meta-analysis included only studies in English that reported odds ratio (OR) data for MetS and SCH. Two researchers combined data using a random-effects model. OR and 95% confidence intervals (CIs) were used to present the results. Results: MetS was associated with an elevated risk of developing SCH (OR 2.56, 95% CI 1.44-4.55). However, the individual components of MetS were not associated with the risk of SCH. Subgroup analysis revealed that different definitions of MetS had varying effects on SCH. Sensitivity analysis confirmed that our results were robust. Conclusions: This meta-analysis indicates that patients with MetS have an increased risk of SCH, while there is no significant association between the five individual components of MetS and the risk of SCH. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023454415.

Clinical study of chemotherapy-related cognitive impairment in patients with non-Hodgkin lymphoma.

BACKGROUND: Chemotherapy for malignant tumors can cause brain changes and cognitive impairment, leading to chemotherapy-induced cognitive impairment (CICI). Current research on CICI has focused on breast cancer and Hodgkin's lymphoma. Whether patients with non-Hodgkin's lymphoma (NHL) undergoing chemotherapy have cognitive impairment has not been fully investigated. AIM: To investigate whether NHL patients undergoing chemotherapy had cognitive impairments. METHODS: The study included 100 NHL patients who were required to complete a comprehensive psychological scale including the Brief Psychiatric Examination Scale (MMSE) at two time points: before chemotherapy and within 2 wk of two chemotherapy courses. A language proficiency test (VFT), Symbol Number Pattern Test (SDMT), Clock Drawing Test (CDT), Abbreviated Daily Cognition Scale (ECog-12), Prospective and Retrospective Memory Questionnaire, and Karnofsky Performance Status were used to assess cognitive changes before and after chemotherapy. RESULTS: The VFT scores for before treatment (BT) and after treatment (AT) groups were 45.20 ± 15.62, and 42.30 ± 17.53, respectively (t -2.16, P < 0.05). The CDT scores were 8 (3.5-9.25) for BT and 7 (2.5-9) for AT groups (Z -2.1, P < 0.05). Retrospective memory scores were 13.5 (9-17) for BT and 15 (13-18) for AT (Z -3.7, P < 0.01). The prospective memory scores were 12.63 ± 3.61 for BT and 14.43 ± 4.32 for AT groups (t -4.97, P < 0.01). The ECog-12 scores were 1.71 (1.25-2.08) for BT and 1.79 (1.42-2.08) for AT groups (Z -2.84, P < 0.01). The SDMT and MMSE values did not show a significant difference between BT and AT groups. CONCLUSION: Compared to the AT group, the BT group showed impaired language, memory, and subjective cognition, but objective cognition and execution were not significantly affected.

Association between Albumin-Corrected Anion Gap and Mortality in Patients with Cardiogenic Shock.

Background: Cardiogenic shock (CS) is a critical illness with a high mortality rate in clinical practice. Although some biomarkers have been found to be associated with mortality in patients suffering from CS in previous studies. The albumin-corrected anion gap (ACAG) has not been studied in depth. Our study aimed to explore the relationship between ACAG and mortality in patients with CS. Methods: All baseline data was extracted from Medical Information Mart for Intensive Care-IV version: 2.0 (MIMIC-IV). According to the prognosis at 30 days of follow-up, they were divided into survivors and non-survivors groups. The survival curves between the two groups were drawn using the Kaplan-Meier method and the log-rank test. Valid factors were selected using the least absolute shrinkage and selection operator (LASSO) logistic analysis model. Analysis was performed to investigate the relationship between mortality and all enrolled patients using restricted cubic spline (RCS) and Cox proportional hazards models. Receiver operating characteristic (ROC) curves were used to assess the predictive ability of ACAG. Evaluation of final result stability using sensitivity analysis. Results: 839 cases were selected to meet the inclusion criteria and categorized into survivors and non-survivors groups in the final analysis. The ACAG value measured for the first time at the time of admission was selected as the research object. Kaplan-Meier (K-M) survival curves showed that cumulative 30- and 90-day survival decreased progressively with elevated ACAG (p < 0.001), and multifactorial Cox regression analyses showed ACAG to be an independent risk factor for increased 30- and 90-day mortality in patients suffering from CS (p < 0.05). RCS curves revealed that all-cause mortality in this group of patients increased with increasing ACAG ( χ 2 = 5.830, p = 0.120). The ROC curve showed that the best cutoff value for ACAG for predicting 30-day mortality in patients with CS was 22.625, with a sensitivity of 44.0% and a specificity of 74.7%. The relationship between ACAG and CS short-term mortality remained stable in all sensitivity analyses (All p < 0.05). Conclusions: The ACAG is an independent risk factor for 30- and 90-day mortality in CS patients and predicts poor clinical outcomes in CS patients. According to our study, elevated ACAG at admission, especially when ACAG > 20 mmol/L, was an independent predictor of all-cause mortality in CS.

Correlation between Lactate Dehydrogenase to Albumin Ratio and the Prognosis of Patients with Cardiac Arrest.

Background: Cardiac arrest (CA) is a common event in the intensive care unit (ICU), which seriously threatens the prognosis of patients. Therefore, it is crucial to determine a simple and effective clinical indicator to judge the prognosis of patients after a CA for later treatments. The purpose of this study was to investigate the relationship between the lactate dehydrogenase to albumin ratio (LAR) and the prognosis of patients after a CA. Methods: The clinical data of participants was obtained from the Medical Information Mart for Intensive Care IV (MIMIC-IV, v2.0; 2008 to 2019). According to the 30-day prognosis, patients were divided into a survivors group (n = 216) and a non-survivors group (n = 304). The optimal LAR threshold was determined using restricted cubic spline (RCS), which divided patients into a high LAR group ( ≥ 15.50, n = 257) and a low LAR group ( < 15.50, n = 263). The ICU hospitalization and 30-day accumulative survival curves of the two groups were plotted following the Kaplan-Meier survival analysis. Multivariate Cox regression was used to analyze the relationship between the LAR and the prognosis of CA patients. Receiver operating characteristic (ROC) curves were drawn to evaluate the predictive efficacy of the LAR on 30-day all-cause mortality, and sensitivity analysis was used to check the reliability of the findings. Results: A total of 520 patients with CA were enrolled and the 30-day mortality was 58.46%. The LAR in the non-survivors group was higher than in the survivors group. The RCS showed a linear trend relationship between the LAR and the mortality risk in patients during their ICU stay and 30 days; moreover, as the LAR increased, so did the risk of mortality. The Kaplan-Meier survival curve showed that compared with the low LAR group, the cumulative survival rates of ICU hospitalization and 30 days were lower in the high LAR group among CA patients (p < 0.001). Multivariate Cox regression analysis showed that an elevated LAR ( ≥ 15.50) was an independent risk factor for mortality during ICU stay and 30 days (p < 0.005). ROC analysis suggested that the LAR was superior to the sequential organ failure assessment (SOFA) score in predicting the 30-day all-cause mortality in CA patients (area under the curve (AUC) = 0.676, 95% confidence interval [CI]: 0.629-0.723). To verify the reliability of our findings, we performed sensitivity analyses and found that the findings were reliable. Conclusions: An elevated LAR might be a predictor of mortality in patients following a CA during ICU hospitalization and 30 days, thereby it can be used to provide a reference for the clinical management of these patients.

Effectiveness of animal-assisted activities and therapies for autism spectrum disorder: a systematic review and meta-analysis.

Background: Given the rising interest in complementary therapeutic strategies for autism spectrum disorder (ASD), this research aims to provide a comprehensive analysis of the impact of animal-assisted activities and therapies (AAAT) on various ASD symptoms. Methods: A meticulous search of databases, including Scopus and PubMed, was conducted to gather relevant research on AAAT for ASD. This process led to the selection of 45 studies encompassing 1,212 participants. The chosen studies were then subjected to a meta-analysis to evaluate the efficacy of AAAT in alleviating core ASD symptoms. Results: The meta-analysis revealed significant improvements in several core ASD symptoms due to AAAT. Notably, there were improvements in social communication (MD = -4.96, 95% CI [-7.49, -2.44]), irritability (MD = -2.38, 95% CI [-4.06, -0.71]), hyperactivity (MD = -4.03, 95% CI [-6.17, -1.89]), and different word usage skills (MD = 20.48, 95% CI [7.41, 33.55]). However, social awareness (MD = -1.63, 95% CI [-4.07, 0.81]), social cognition (MD = -3.60, 95% CI [-9.36, 2.17]), social mannerisms (MD = -0.73, 95% CI [-2.55, 1.09]), social motivation (MD = -1.21, 95% CI [-2.56, 0.13]), lethargy (MD = -1.12, 95% CI [-3.92, 1.68]), and stereotypical behaviors (MD = -0.23, 95% CI [-1.27, 0.80]) did not significantly improve. Conclusion: The study demonstrates the potential of AAAT in improving certain core symptoms of ASD, such as social communication, irritability, hyperactivity, and word usage skills. However, the effectiveness of AAAT in other ASD symptom domains remains uncertain. The research is limited by the absence of long-term follow-up data and a high risk of bias in existing studies. Therefore, while the findings indicate the promise of AAAT in specific areas, caution is advised in generalizing its efficacy across all ASD symptoms.

Global prevalence of Borrelia burgdorferi and Anaplasma phagocytophilum coinfection in Ixodes tick populations: protocol for a systematic review and meta-analysis.

INTRODUCTION: Ixodes ticks are pivotal in transmitting diseases like Lyme disease and human granulocytic anaplasmosis, caused by Borrelia burgdorferi and Anaplasma phagocytophilum, respectively. These pathogens not only affect humans through single or multiple tick bites but also pose risks to animal hosts, leading to potential coinfections. Despite regional studies indicating significant prevalence, their global coinfection data remain sparse. This study aims to bridge this gap through a systematic review and meta-analysis of B. burgdorferi and A. phagocytophilum coinfections in Ixodes ticks worldwide. Addressing data limitations and study variability, it seeks to provide a nuanced understanding of coinfection patterns, their epidemiological implications and inform targeted prevention strategies. METHODS AND ANALYSIS: Following Preferred Reporting Items for Systematic Review and Meta-analysis Protocols 2015 guidelines and PROSPERO registration, this study will undertake a thorough database search without constraints on language or publication date, using standardised screening and data extraction protocols. The quality and bias of studies will be evaluated using Joanna Briggs Institute tools. In the statistical analysis phase, conducted in R, we will initially determine the use of fixed or random-effects models based on the assessment of data heterogeneity. This choice will guide the framework for subsequent analyses. Within the selected model's framework, we will perform subgroup analyses and meta-regression to investigate the effects of various factors, ensuring that each step is tailored to the initial model selection to maintain analytical consistency. ETHICS AND DISSEMINATION: As this study does not involve clinical research or data collection from subjects, ethical approval is not required. We will uphold ethical standards in synthesising and reporting data. Study outcomes will be published in peer-reviewed journals, communicating findings to the scientific community and contributing to the understanding of Ixodes tickborne diseases. PROSPERO REGISTRATION NUMBER: CRD42023449735.

Rapid Mold Detection in Chinese Herbal Medicine Using Enhanced Deep Learning Technology.

Mold contamination poses a significant challenge in the processing and storage of Chinese herbal medicines (CHM), leading to quality degradation and reduced efficacy. To address this issue, we propose a rapid and accurate detection method for molds in CHM, with a specific focus on Atractylodes macrocephala, using electronic nose (e-nose) technology. The proposed method introduces an eccentric temporal convolutional network (ETCN) model, which effectively captures temporal and spatial information from the e-nose data, enabling efficient and precise mold detection in CHM. In our approach, we employ the stochastic resonance (SR) technique to eliminate noise from the raw e-nose data. By comprehensively analyzing data from eight sensors, the SR-enhanced ETCN (SR-ETCN) method achieves an impressive accuracy of 94.3%, outperforming seven other comparative models that use only the response time of 7.0 seconds before the rise phase. The experimental results showcase the ETCN model's accuracy and efficiency, providing a reliable solution for mold detection in Chinese herbal medicine. This study contributes significantly to expediting the assessment of herbal medicine quality, thereby helping to ensure the safety and efficacy of traditional medicinal practices.

Effects of different selenium biofortification methods on Pleurotus eryngii polysaccharides: Structural characteristics, antioxidant activity and binding capacity in vitro.

The effects of selenium biofortification methods involving sodium selenite and selenium yeast on the structural characteristics, antioxidant activity and binding capacity of Pleurotus eryngii polysaccharides were investigated. Sodium selenite Se-enriched Pleurotus eryngii polysaccharides (Se-SPEP), selenium yeast Se-enriched Pleurotus eryngii polysaccharides (Se-YPEP), and Pleurotus eryngii polysaccharides (PEP) had Se contents of 20.548 ± 1.561, 19.822 ± 0.613, and 0.052 ± 0.016 µg/g, respectively. Compared with PEP, Se-SPEP and Se-YPEP had lower molecular weight and contained the same monosaccharides in varying molar ratios. The results of FT-IR, PS, ZP, and SEM indicated significant alterations in structural characteristics following selenium biofortification. Se-PEPs exhibited superior activity against ABTS, DPPH, and ·OH radicals, as well as the higher binding capacity for Cd2+ and Cu2+ compared to natural polysaccharides. The binding capacity of the polysaccharides for Cd2+ and Cu2+ was higher at pH 6.8 compared to pH 2.0, while the opposite was observed for Pb2+. Furthermore, Se-PEPs exhibited a significantly higher binding capacity for Cd2+ and Cu2+ at both pH levels compared to natural polysaccharides (P < 0.05). Se-YPEP displayed higher antioxidant activity than Se-SPEP, with their binding capacities reversed. These data indicated that selenium biofortification methods have different positive impacts on the structure and activity of polysaccharides compared to natural polysaccharides, making Se-PEPs promising dietary supplements for safeguarding the body against the risks posed by food-derived heavy metals.

Dietary sanguinarine supplementation recovers the decrease in muscle quality and nutrient composition induced by high-fat diets of grass carp (Ctenopharyngodon idella).

The intake of high-fat diets (HFD) has been shown to diminish the muscle quality of aquatic animals. Sanguinarine, as an excellent additive, exhibits the capability to reduce fat deposition and alleviate inflammation. However, its role in the muscle quality reduction caused by HFD remains unclear. An eight-week trial was conducted to investigate the impacts of dietary supplementation of sanguinarine at 1200 µg/kg (HFDS; crude fat = 10%) on the muscle quality of grass carp (Ctenopharyngodon idellus) in comparison to a basic diet (CON, crude fat = 5%). Each group had 3 replicates, with 40 fish per replicate. This experiment employed one-way ANOVA and Duncan's multiple comparisons of the means. The results showed that the HFD exhibited lower growth performance, reduced protein deposition, myofiber diameter, and muscle hardness, coupled with higher levels of fat deposition and inflammation when compared with the CON. However, HFDS improved growth performance (P < 0.05), fat metabolism (ppar-α ( P = 0.001), lpl (P < 0.001), atgl (P < 0.001), and cpt1 (P = 0.001) expression exhibited a significant elevation), protein deposition (the protein and mRNA levels of AKT (P = 0.004), PI3K (P = 0.027), TOR (P = 0.005), and P70S6K (P = 0.007) demonstrated a marked increase), myofiber diameter, muscle hardness, and the total content of eicosapentaenoic acid and docosahexaenoic acid. Furthermore, the HFDS reduced oxidative damage caused by fat deposition by significantly downregulating nf-κb (P < 0.001), il-1ß (P < 0.001), il-6 (P < 0.001), il-8 (P = 0.003), and tnf-α (P < 0.001) expression and markedly upregulated nrf2 (P < 0.001), gpx4 (P < 0.001), cat (P < 0.001), sod (P < 0.001), and gr (P = 0.003) expression. The findings from this study suggest that sanguinarine has the potential to alleviate the adverse effects of HFD on growth and muscle quality, providing a theoretical foundation for its practical implementation.

Rigid Fe(III) Chelate with Phosphonate Pendants: A Stable and Effective Extracellular MRI Contrast Agent.

A novel Fe(III) complex, Fe-tBPCDTA, was synthesized and explored as a potential contrast agent for MRI. Compared to established agents like Fe-EDTA and Fe-tCDTA, Fe-tBPCDTA exhibited moderate relaxivity (r1 = 1.17 s-1·mmol-1) due to its enhanced second-sphere mechanism. It also displayed improved kinetic inertness, lower cytotoxicity, and enhanced redox stability. In vivo studies demonstrated its function as an extracellular fluid agent, providing tumor contrast comparable to that of Gd-DTPA at a higher dosage. Complete renal clearance occurred within 24 h. These findings suggest Fe-tBPCDTA as a promising candidate for further development as a safe and effective extracellular MRI contrast agent.

The prevalence and its associated factors of psychological stress among middle school students in China: pooled evidence from a systematic scoping review.

Psychological issues are of significant concern in present-day society, as poor mental well-being results in depression and suicidal behavior. Understanding the current situation of psychological stress among secondary school students will help policy makers to formulate targeted measures to help them cope with stress, and at the same time evaluate the effectiveness of the existing policies to address the shortcomings and enhance the diversification of interventions. The main purpose of this review was to map the existing evidence on the prevalence and levels of psychological stress among adolescents in China, and to identify the associated risk factors. This review strictly adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A comprehensive search was performed spanning Web of Science, PubMed, and Scopus databases. Studies involving only humans and full text in English were selected. Selection was limited to samples from mainland China, Hong Kong, Macau, and Taiwan. Variables were extracted, exploring the factors that affected the mental wellness of Chinese middle school students. A final 15 articles and 1 report were included. The findings revealed psychological stress is prevalent among Chinese middle school population, with the degree of prevalence from low to severe stress levels. Three dimensions of psychological stress affecting Chinese secondary school students: school, family and lifestyle. Within the school, the factors included academic stress, peer relationships etc. Family-related factors were comprised of parent-child relationship, parents' mental health status etc. Lastly, lifestyle-related factors included poor diet, sedentary and inactivity etc. Our findings suggest that policy makers should reduce the excessive emphasis on examination results and focus on the all-round development of students, and that schools should organize a variety of extra-curricular activities to reduce students' stress. Parents should create a harmonious family atmosphere to minimize conflicts and maintain close communication with teachers. Systematic Review Registration: OSF; https://doi.org/10.17605/OSF.IO/HEFCP.