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This study intends to evaluate the utilization potential of the combined Raman spectroscopy and machine learning approach to quickly identify the rainbow trout adulteration in Atlantic salmon. The adulterated samples contained various concentrations (0-100% w/w at 10% intervals) of rainbow trout mixed into Atlantic salmon. Spectral preprocessing methods, such as first derivative, second derivative, multiple scattering correction (MSC), and standard normal variate, were employed. Unsupervised algorithms, such as recursive feature elimination, genetic algorithm (GA), and simulated annealing, and supervised K-means clustering (KM) algorithm were used for selecting important spectral bands to reduce the spectral complexity and improve the model stability. Finally, the performances of various machine learning models, including linear regression, nonlinear regression, regression tree, and rule-based models, were verified and compared. The results denoted that the developed GA-KM-Cubist machine learning model achieved satisfactory results based on MSC preprocessing. The determination coefficient (R2) and root mean square error of prediction sets (RMSEP) in the test sets were 0.87 and 10.93, respectively. These results indicate that Raman spectroscopy can be used as an effective Atlantic salmon adulteration identification method; further, the developed model can be used for quantitatively analyzing the rainbow trout adulteration in Atlantic salmon.
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Aprendizado de Máquina , Oncorhynchus mykiss/classificação , Salmo salar/classificação , Análise Espectral Raman , Tecido Adiposo/química , AnimaisRESUMO
BACKGROUND: After the 2009 influenza A(H1N1)pdm09 pandemic, China established its first severe acute respiratory infections (SARI) sentinel surveillance system. METHODS: We analyzed data from SARI cases in 10 hospitals in 10 provinces in China from February 2011 to October 2013. RESULTS: Among 5,644 SARI cases, 330 (6%) were influenza-positive. Among these, 62% were influenza A and 38% were influenza B. Compared with influenza-negative cases, influenza-positive SARI cases had a higher median age (20.0 years vs.11.0, p=0.003) and were more likely to have at least one underlying chronic medical condition (age adjusted percent: 28% vs. 25%, p<0.001). The types/subtypes of dominant strains identified by SARI surveillance was almost always among dominant strains identified by the influenza like illness (ILI) surveillance system and influenza activity in both systems peaked at the same time. CONCLUSIONS: Data from China's first SARI sentinel surveillance system suggest that types/subtypes of circulating influenza strains and epidemic trends among SARI cases were similar to those among ILI cases.
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Vírus da Influenza A/isolamento & purificação , Vírus da Influenza B/isolamento & purificação , Influenza Humana/epidemiologia , Vigilância de Evento Sentinela , Doença Aguda , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Pré-Escolar , China/epidemiologia , Feminino , Humanos , Lactente , Recém-Nascido , Vírus da Influenza A Subtipo H1N1/isolamento & purificação , Influenza Humana/diagnóstico , Influenza Humana/virologia , Masculino , Pessoa de Meia-Idade , Índice de Gravidade de Doença , Adulto JovemRESUMO
INTRODUCTION: Cardiac surgery is related to an increased risk of postoperative acute kidney injury (AKI). Serum soluble ST2 (sST2) is highly predictive of several cardiovascular diseases and may also be involved in renal injury. This study explored the relationship between serum sST2 levels measured at ICU admission and the development of AKI after cardiac surgery. METHODS: We prospectively conducted an investigation on consecutive patients who underwent cardiac surgery. sST2 was immediately measured at ICU admission. The relationship between the levels of sST2 and the development of AKI was explored using stepwise logistic regression. RESULTS: Among the 500 patients enrolled, AKI was observed in 207 (41%) patients. Serum sST2 levels in AKI patients were higher than those without AKI (61.46 ng/ml [46.52, 116.25] versus 38.91 ng/ml [28.74, 50.93], P < 0.001). Additionally, multivariable logistic regression analysis showed that as progressively higher tertiles of serum sST2, the odds ratios (ORs) of AKI gradually increased (adjusted ORs of 1.97 [95% CI, 1.13-3.45], and 4.27 [95% CI, 2.36-7.71] for tertiles 2 and 3, respectively, relative to tertile 1, P < 0.05). The addition of sST2 further improved reclassification (P < 0.001) and discrimination (P < 0.001) over the basic model, which included established risk factors. CONCLUSION: Serum sST2 levels at ICU admission were associated with the development of postoperative AKI and improved the identification of AKI after cardiac surgery.
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Background: The occurrence of acute kidney injury (AKI) following cardiac surgery is common and linked to unfavorable consequences while identifying it in its early stages remains a challenge. The aim of this research was to examine whether the fibrinogen-to-albumin ratio (FAR), an innovative inflammation-related risk indicator, has the ability to predict the development of AKI in individuals after cardiac surgery. Methods: Patients who underwent cardiac surgery from February 2023 to March 2023 and were admitted to the Cardiac Surgery Intensive Care Unit of a tertiary teaching hospital were included in this prospective observational study. AKI was defined according to the KDIGO criteria. To assess the diagnostic value of the FAR in predicting AKI, calculations were performed for the area under the receiver operating characteristic curve (AUC), continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: Of the 260 enrolled patients, 85 developed AKI with an incidence of 32.7%. Based on the multivariate logistic analyses, FAR at admission [odds ratio (OR), 1.197; 95% confidence interval (CI), 1.064-1.347, p = 0.003] was an independent risk factor for AKI. The receiver operating characteristic (ROC) curve indicated that FAR on admission was a significant predictor of AKI [AUC, 0.685, 95% CI: 0.616-0.754]. Although the AUC-ROC of the prediction model was not substantially improved by adding FAR, continuous NRI and IDI were significantly improved. Conclusions: FAR is independently associated with the occurrence of AKI after cardiac surgery and can significantly improve AKI prediction over the clinical prediction model.
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Background: Considerable morbidity and death are associated with acute kidney damage (AKI) following total aortic arch replacement (TAAR). The relationship between AKI following TAAR and serum magnesium levels remains unknown. The intention of this research was to access the predictive value of serum magnesium levels on admission to the Cardiovascular Surgical Intensive Care Unit (CSICU) for AKI in patients receiving TAAR. Methods: From May 2018 to January 2020, a prospective, observational study was performed in the Guangdong Provincial People's Hospital CSICU. Patients accepting TAAR admitted to the CSICU were studied. The Kidney Disease: Improving Global Outcomes (KDIGO) definition of serum creatinine was used to define AKI, and KDIGO stages two or three were used to characterize severe AKI. Multivariable logistic regression and area under the curve receiver-operator characteristic curve (AUC-ROC) analysis were conducted to assess the predictive capability of the serum magnesium for AKI detection. Finally, the prediction model for AKI was established and internally validated. Results: Of the 396 enrolled patients, AKI occurred in 315 (79.5%) patients, including 154 (38.8%) patients with severe AKI. Serum magnesium levels were independently related to the postoperative AKI and severe AKI (both, P < 0.001), and AUC-ROCs for predicting AKI and severe AKI were 0.707 and 0.695, respectively. Across increasing quartiles of serum magnesium, the multivariable-adjusted odds ratios (95% confidence intervals) of postoperative AKI were 1.00 (reference), 1.04 (0.50-2.82), 1.20 (0.56-2.56), and 6.19 (2.02-23.91) (P for Trend < 0.001). When serum magnesium was included to a baseline model with established risk factors, AUC-ROC (0.833 vs 0.808, P = 0.050), reclassification (P < 0.001), and discrimination (P = 0.002) were further improved. Conclusions: Serum magnesium levels on admission are an independent predictor of AKI. In TAAR patients, elevated serum magnesium levels were linked to an increased risk of AKI. In addition, the established risk factor model for AKI can be considerably improved by the addition of serum magnesium in TAAR patients hospitalized in the CSICU.
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Background: Severe acute kidney injury (AKI) after total aortic arch replacement (TAAR) is related to adverse outcomes in patients with acute type A aortic dissection (ATAAD). However, the early prediction of severe AKI remains a challenge. This study aimed to develop a novel model to predict severe AKI after TAAR in ATAAD patients using machine learning algorithms. Methods: A total of 572 ATAAD patients undergoing TAAR were enrolled in this retrospective study, and randomly divided into a training set (70 %) and a validation set (30 %). Lasso regression, support vector machine-recursive feature elimination and random forest algorithms were used to screen indicators for severe AKI (defined as AKI stage III) in the training set, respectively. Then the intersection indicators were selected to construct models through artificial neural network (ANN) and logistic regression. The AUC-ROC curve was employed to ascertain the prediction efficacy of the ANN and logistic regression models. Results: The incidence of severe AKI after TAAR was 22.9 % among ATAAD patients. The intersection predictors identified by different machine learning algorithms were baseline serum creatinine and ICU admission variables, including serum cystatin C, procalcitonin, aspartate transaminase, platelet, lactic dehydrogenase, urine N-acetyl-ß-d-glucosidase and Acute Physiology and Chronic Health Evaluation II score. The ANN model showed a higher AUC-ROC than logistic regression (0.938 vs 0.908, p < 0.05). Furthermore, the ANN model could predict 89.1 % of severe AKI cases beforehand. In the validation set, the superior performance of the ANN model was further confirmed in terms of discrimination ability (AUC = 0.916), calibration curve analysis and decision curve analysis. Conclusion: This study developed a novel and reliable clinical prediction model for severe AKI after TAAR in ATAAD patients using machine learning algorithms. Importantly, the ANN model showed a higher predictive ability for severe AKI than logistic regression.
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When intelligent mobile robots perform global path planning in complex and narrow environments, several issues often arise, including low search efficiency, node redundancy, non-smooth paths, and high costs. This paper proposes an improved path planning algorithm based on the rapidly exploring random tree (RRT) approach. Firstly, the target bias sampling method is employed to screen and eliminate redundant sampling points. Secondly, the adaptive step size strategy is introduced to address the limitations of the traditional RRT algorithm. The mobile robot is then modeled and analyzed to ensure that the path adheres to angle and collision constraints during movement. Finally, the initial path is pruned, and the path is smoothed using a cubic B-spline curve, resulting in a smoother path with reduced costs. The evaluation metrics employed include search time, path length, and the number of sampling nodes. To evaluate the effectiveness of the proposed algorithm, simulations of the RRT algorithm, RRT-connect algorithm, RRT* algorithm, and the improved RRT algorithm are conducted in various environments. The results demonstrate that the improved RRT algorithm reduces the generated path length by 25.32% compared to the RRT algorithm, 26.42% compared to the RRT-connect algorithm, and 4.99% compared to the RRT* algorithm. Moreover, the improved RRT algorithm significantly improves the demand for reducing path costs. The planning time of the improved RRT algorithm is reduced by 64.96% compared to that of the RRT algorithm, 40.83% compared to that of the RRT-connect algorithm, and 27.34% compared to that of the RRT* algorithm, leading to improved speed. These findings indicate that the proposed method exhibits a notable improvement in the three crucial evaluation metrics: sampling time, number of nodes, and path length. Additionally, the algorithm performed well after undergoing physical verification with an insect-like mobile robot in a real environment featuring narrow elevator entrances.
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BACKGROUND: Calcium plays a key role in many bio-homeostasis functions. Previous studies indicated that serum calcium is associated with diseases such as anaemia. However, the evidence on the association between serum calcium levels and anaemia risk is limited. Thus, the purpose of our study is to investigate the relationship between serum calcium and anaemia in US adults. METHODS: This cross-sectional study used data from the National Health and Nutrition Examination Survey (NHANES) including 15,519 participants, aged ≥18 years. The analyses were performed using multivariate logistic regression and a generalized additive model (GAM). Subgroup analysis, stratified by gender and age, was also performed. RESULTS: Among the sample of 15,519 individuals, 1565 (10.8%) had been diagnosed with anaemia. Both the univariate logistic regression model and multivariate logistic regression model showed a reverse relationship between serum calcium and anaemia risk. Moreover, a non-linear association between serum calcium and anaemia risk was observed using GAM and smooth curve fitting. The inflection point of serum calcium was at 2.3â mmol/L. GAM with penalized splines suggested a reverse association between serum calcium and the prevalence of anaemia when the concentration of serum calcium was below 2.3â mmol/L. In contrast, we found no statistically significant difference when serum calcium concentration was higher than the inflection point (2.3â mmol/L). CONCLUSION: Lower serum calcium levels were associated with increased risk of anaemia risk. Moreover, we observed non-linear associations between serum calcium and anaemia risk. Our results need to be confirmed in future prospective studies.
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Anemia , Cálcio , Humanos , Adulto , Adolescente , Inquéritos Nutricionais , Estudos Transversais , Anemia/epidemiologiaRESUMO
Objective: Pelvic floor dysfunction (PFD) is highly prevalent among women. Pelvic floor ultrasound (PFU) is a critical method for assessing PFD. This study examined the knowledge, attitudes, and practice (KAP) of women of childbearing age regarding PFD and PFU. Methods: This cross-sectional study was conducted between August 18, 2022, and September 20, 2022, in Sichuan, China. A total of 504 women of childbearing age participated in this study. A self-administered questionnaire was developed to assess KAP regarding PFD and PFU. Univariable and multivariable logistic regression analyses were conducted to assess the association between demographic characteristics and KAP. Results: The average scores for knowledge, attitudes, and practice were 12.53, 39.98, and 16.51 out of 17, 45, and 20, respectively. Despite adequate knowledge of PFD symptoms, aging-related risks, and PFD harms (correct rates > 80%), participants showed poor knowledge about the benefits of PFU, PFU types, and Kegel exercise (correct rates < 70%). High scores in knowledge and attitude (odds ratio = 1.23 and 1.11, P < 0.001 and P = 0.005, respectively) were independent predictors of good practice, while never having been pregnant (odds ratio = 0.10, P < 0.001), alcohol consumption (odds ratio = 0.09, P = 0.027), and not being diagnosed with PFD or an unclear diagnosis independently predicted poor practice (both odds ratio = 0.03, both P < 0.001). Conclusion: Women of childbearing age in Sichuan, China, showed moderate knowledge, positive attitude, and good practice regarding PFD and PFU. Knowledge, attitude, pregnancy history, alcohol consumption, and PFD diagnosis are associated with practice.
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Distúrbios do Assoalho Pélvico , Gravidez , Humanos , Feminino , Distúrbios do Assoalho Pélvico/diagnóstico por imagem , Distúrbios do Assoalho Pélvico/complicações , Diafragma da Pelve , Estudos Transversais , Conhecimentos, Atitudes e Prática em Saúde , Inquéritos e QuestionáriosRESUMO
Understanding molecular mechanisms during protein modification is critical for expanding the application of plant proteins. This study investigated the conformational change and molecular mechanism of pea protein isolate (PPI) under pulsed electric field (PEF)-assisted (-)-Epigallocatechin-Gallate (EGCG) modification. The flexibility of PPI was significantly enhanced after PEF treatment (10 kV/cm) with decrease (23.25 %) in α-helix and increase (117.25 %) in random coil. The binding constant and sites of PEF-treated PPI with EGCG were increased by 2.35 times and 10.00 % (308 K), respectively. Molecular docking verified that PEF-treated PPI had more binding sites with EGCG (from 4 to 10). The number of amino acid residues involved in hydrophobic interactions in PEF-treated PPI-EGCG increased from 5 to 13. PEF-treated PPI-EGCG showed a significantly increased antioxidant activity compared to non-PEF-treated group. This work revealed the molecular level of PEF-assisted EGCG modification of PPI, which will be significant for the application of PPI in food industry.
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Proteínas de Ervilha , Simulação por Computador , Simulação de Acoplamento Molecular , Análise Espectral , Antioxidantes/farmacologia , Antioxidantes/químicaRESUMO
Intestinal ischemia/reperfusion (I/R) injury is a grave condition with high morbidity and mortality. We previously confirmed that intestinal I/R induces intestinal flora disorders and changes in metabolites, but the role of different metabolites in intestinal I/R injury is currently unclear. Based on targeted metabolic sequencing, pravastatin (PA) was determined to be a metabolite of the gut microbiota. Further, intestinal I/R model mice were established through superior mesenteric artery obstruction. In addition, a co-culture model of small intestinal organoids and type II innate lymphoid cells (ILC2s) was subjected to hypoxia/reoxygenation (H/R) to simulate an intestinal I/R model. Moreover, correlation analysis between the PA level in preoperative feces of patients undergoing cardiopulmonary bypass and the indices of postoperative intestinal I/R injury was carried out. IL-33-deficient mice, ILC2-deleted mice, and anti-IL-13 neutralizing antibodies were also used to explore the potential mechanism through which PA attenuates intestinal I/R injury. We demonstrated that PA levels in the preoperative stool of patients undergoing cardiopulmonary bypass were negatively correlated with the indices of postoperative intestinal I/R injury. Furthermore, PA alleviated intestinal I/R injury and improved the survival of mice. We further showed that PA promotes IL-13 release from ILC2s by activating IL-33/ST2 signaling to attenuate intestinal I/R injury. In addition, IL-13 promoted the self-renewal of intestinal stem cells by activating Notch1 and Wnt signals. Overall, results indicated that the gut microbial metabolite PA can attenuate intestinal I/R injury by promoting the release of IL-13 from ILC2s via IL-33/ST2 signaling, revealing a novel mechanism of and therapeutic strategy for intestinal I/R injury.
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Microbioma Gastrointestinal/imunologia , Imunidade Inata , Proteína 1 Semelhante a Receptor de Interleucina-1/imunologia , Interleucina-13/imunologia , Interleucina-33/imunologia , Enteropatias/imunologia , Linfócitos/imunologia , Pravastatina/imunologia , Animais , Modelos Animais de Doenças , Humanos , Proteína 1 Semelhante a Receptor de Interleucina-1/genética , Interleucina-13/genética , Interleucina-33/genética , Enteropatias/genética , Masculino , Camundongos , Camundongos Knockout , Traumatismo por ReperfusãoRESUMO
Deep-sea hydrothermal vent chimneys harbor a high diversity of largely unknown microorganisms. Although the phylogenetic diversity of these microorganisms has been described previously, the adaptation and metabolic potential of the microbial communities is only beginning to be revealed. A pyrosequencing approach was used to directly obtain sequences from a fosmid library constructed from a black smoker chimney 4143-1 in the Mothra hydrothermal vent field at the Juan de Fuca Ridge. A total of 308,034 reads with an average sequence length of 227 bp were generated. Comparative genomic analyses of metagenomes from a variety of environments by two-way clustering of samples and functional gene categories demonstrated that the 4143-1 metagenome clustered most closely with that from a carbonate chimney from Lost City. Both are highly enriched in genes for mismatch repair and homologous recombination, suggesting that the microbial communities have evolved extensive DNA repair systems to cope with the extreme conditions that have potential deleterious effects on the genomes. As previously reported for the Lost City microbiome, the metagenome of chimney 4143-1 exhibited a high proportion of transposases, implying that horizontal gene transfer may be a common occurrence in the deep-sea vent chimney biosphere. In addition, genes for chemotaxis and flagellar assembly were highly enriched in the chimney metagenomes, reflecting the adaptation of the organisms to the highly dynamic conditions present within the chimney walls. Reconstruction of the metabolic pathways revealed that the microbial community in the wall of chimney 4143-1 was mainly fueled by sulfur oxidation, putatively coupled to nitrate reduction to perform inorganic carbon fixation through the Calvin-Benson-Bassham cycle. On the basis of the genomic organization of the key genes of the carbon fixation and sulfur oxidation pathways contained in the large genomic fragments, both obligate and facultative autotrophs appear to be present and contribute to biomass production.