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The current research examined the impact of different concentrations of oat beta-glucan (OG) on the in vitro digestibility of fava bean starch (FS). Our pasting analysis demonstrated that OG effectively decreased the viscosity and regrowth of FS, suppressing its in situ regrowth while enhancing the in vitro pasting temperature. Moreover, OG markedly diminished amylose leaching and minimized the particle size of the pasted starch. Rheological and textural evaluations demonstrated that OG markedly diminished the viscoelasticity of the starch and softened the gel strength of the composite system. Structural analysis revealed that hydrogen bonding is the primary interaction in the FS-OG system, indicating that OG interacts with amylose through hydrogen bonding, thereby delaying starch pasting and enhancing the gelatinization characteristics of FS gels. Notably, the incorporation of OG resulted in a reduction in the levels of rapidly digestible starch (RDS) and slowly digestible starch (SDS) in FS, accompanied by a notable increase in resistant starch (RS) content, from 21.30% to 31.82%. This study offers crucial insights for the application of OG in starch-based functional foods.

Understanding the oceanic carbon cycle, particularly in the Arctic regions, is crucial for addressing climate change. However, significant research gaps persist, especially regarding climate effects on the oceanic carbon cycle in these regions. This review systematically explores Arctic-related research, focusing on mechanisms, regulatory frameworks, and modelling approaches in the oceanic carbon cycle, carbon sink, climate change impact, and maritime shipping. The findings highlight the Arctic’s limited observer presence and high operational costs, hindering the data availability and studies on carbon-cycle changes. This underscores the need to integrate real-time Arctic Ocean monitoring data. Carbon sink research urgently requires direct methods to measure anthropogenic carbon uptake and address uncertainties in air–ocean carbon fluxes due to sea ice melting. Unlike terrestrial carbon cycling research, carbon-cycle studies in the oceans, which are essential for absorbing anthropogenic emissions, receive insufficient attention, especially in the Arctic regions. Numerous policies often fall short in achieving effective mitigation, frequently depending on voluntary or market-based approaches. Analyzing carbon-cycle and sink models has uncovered limitations, primarily due to their global perspective, hampering in-depth assessments of climate change effects on the Arctic regions. To pave the way for future research, enhancing Arctic Ocean climate data availability is recommended, as well as fostering international cooperation in carbon-cycle research, enforcing carbon policies, and improving regional modelling in the Arctic Ocean.

The aim of this study was to identify predictive immunity/hypoxia/ferroptosis/epithelial mesenchymal transformation (EMT)-related biomarkers, pathways and new drugs in allograft rejection in kidney transplant patients. First, gene expression data were downloaded followed by identification of differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) analysis. Second, diagnostic model was construction based on key genes, followed by correlation analysis between immune/hypoxia/ferroptosis/EMT and key diagnostic genes. Finally, drug prediction of diagnostic key genes was carried out. Five diagnostic genes were further identified, including CCR5, CD86, CD8A, ITGAM, and PTPRC, which were positively correlated with allograft rejection after the kidney transplant. Highly infiltrated immune cells, highly expression of hypoxia-related genes and activated status of EMT were significantly positively correlated with five diagnostic genes. Interestingly, suppressors of ferroptosis (SOFs) and drivers of ferroptosis (DOFs) showed a complex regulatory relationship between ferroptosis and five diagnostic genes. CD86, CCR5, and ITGAM were respectively drug target of ABATACEPT, MARAVIROC, and CLARITHROMYCIN. PTPRC was drug target of both PREDNISONE and EPOETIN BETA. In conclusion, the study could be useful in understanding changes in the microenvironment within transplantation, which may promote or sustain the development of allograft rejection after kidney transplantation.

Abstract Background Circular RNA (circRNA) and N6‐methyladenosine (m6A) play a critical role in tumour occurrence and development, including colorectal cancer (CRC). However, little is known about the interaction between circRNA and m6A in the radiosensitivity of CRC. Here, we investigated the role of a novel m6A‐regulated circRNA in CRC. Methods Differentially expressed circRNAs from radiosensitive and radioresistant CRC tissues were screened. Modifications of the selected circRNAs were examined by methylated RNA immunoprecipitation assay. Finally, the selected circRNAs were subjected to radiosensitivity assay. Results We identified that circAFF2 is closely related to both radiosensitivity and m6A in CRC. CircAFF2 was highly expressed in patients with radiosensitive rectal cancer, and patients with high expression of circAFF2 had a better prognosis. In addition, circAFF2 can enhance the radiosensitivity of CRC cells both in vitro and in vivo. The regulation of circAFF2 involves ALKBH5‐mediated demethylation, followed by its recognition and degradation via YTHDF2. Rescue experiments revealed that circAFF2 could reverse the radiosensitivity induced by ALKBH5 or YTHDF2. Mechanistically, circAFF2 binds with CAND1, promotes the binding of CAND1 to Cullin1 and inhibits its neddylation, subsequently impacting the radiosensitivity of CRC. Conclusion We identified and characterised circAFF2 as a novel m6A‐modified circRNA and validated the ALKBH5/YTHDF2/circAFF2/Cullin‐NEDD8 axis as a potential radiotherapy target for CRC.

The aim of this work is to analyze the clinicopathological characteristics and prognostic factors of patients with nuclear pedigree of esophageal cancer. The clinicopathological data and follow-up information of 3,260 patients from different nuclear pedigree of esophageal cancer who underwent radical resection of esophageal cancer were collected, and the clinicopathological characteristics and prognostic factors of the patients were analyzed. The male to female ratio of 3,260 patients with esophageal cancer was 1.7:1. The diagnosis age was ranged from 32 to 85 (60.2 ± 8.1) years old. About 53.8% of the patients were ≥ 60 years old; About 88.8% of the patients came from the high incidence area of esophageal cancer; About 82.5% of the tumors were located in the middle and lower segments of esophagus; Poor, moderate and well differentiation accounted for 26.6%, 61.9% and 11.5% respectively; The surgical margin accounted for 94.3%; 47.6% of the tumors were shorter than 4 cm in length; Clinicopathological TNM stage (0+I) accounted for 15.2%, and stage II, III and IV accounted for 54.5%, 29.9% and 0.4%, respectively. Cox analysis showed that male, diagnosed age ≥ 60 years, tumor located in neck and upper esophageal segments, poor differentiation, tumor length ≥ 4 cm, and advanced TNM were independent risk factors for the prognosis of patients in nuclear pedigree with esophageal cancer. Gender, diagnosis age, tumor location, degree of differentiation, tumor length and TNM stage are the influencing factors for the prognosis of patients with nuclear pedigree of esophageal cancer, which will provide important data for the future study of esophageal cancer family aggregation.

Abstract Radiotherapy is among the routine treatment options for malignant tumors. And it damages DNA and other cellular organelles in target cells by using ionizing radiation produced by various rays, killing the cells. In recent years, multiple studies have demonstrated that exosomes are mechanistically involved in regulating tumor formation, development, invasion and metastasis, and immune evasion. The latest research shows that radiation can affect the abundance and composition of exosomes as well as cell-to-cell communication. In the environment, exosome-carried miRNAs, circRNA, mRNA, and proteins are differentially expressed in cancer cells, while these molecules play a role in numerous biological processes, including the regulation of oncogene expression, mediation of signaling pathways in cancer cells, remodeling of tumor-related fibroblasts, regulation of cell radiosensitivity, and so forth. Therefore, elucidation of the mechanism underlying the role of exosomes in radiotherapy of malignant tumors is crucial for improving the efficacy of radiotherapy. This review will summarize the research advances in radiosensitivity of malignant tumors related to exosomes.

As clinical understanding of pediatric Post-Acute Sequelae of SARS CoV-2 (PASC) develops, and hence the clinical definition evolves, it is desirable to have a method to reliably identify patients who are likely to have post-acute sequelae of SARS CoV-2 (PASC) in health systems data. In this study, we developed and validated a machine learning algorithm to classify which patients have PASC (distinguishing between Multisystem Inflammatory Syndrome in Children (MIS-C) and non-MIS-C variants) from a cohort of patients with positive SARS- CoV-2 test results in pediatric health systems within the PEDSnet EHR network. Patient features included in the model were selected from conditions, procedures, performance of diagnostic testing, and medications using a tree-based scan statistic approach. We used an XGboost model, with hyperparameters selected through cross-validated grid search, and model performance was assessed using 5-fold cross-validation. Model predictions and feature importance were evaluated using Shapley Additive exPlanation (SHAP) values. The model provides a tool for identifying patients with PASC and an approach to characterizing PASC using diagnosis, medication, laboratory, and procedure features in health systems data. Using appropriate threshold settings, the model can be used to identify PASC patients in health systems data at higher precision for inclusion in studies or at higher recall in screening for clinical trials, especially in settings where PASC diagnosis codes are used less frequently or less reliably. Analysis of how specific features contribute to the classification process may assist in gaining a better understanding of features that are associated with PASC diagnoses.

Abstract Background: Electronic health record (EHR) data have many quality problems that may affect the outcome of research results and decision support systems. Many methods have been used to evaluate EHR data quality. However, there has yet to be a consensus on the best practice. We used a rule-based approach to assess the variability of EHR data quality across multiple healthcare systems. Methods: To quantify data quality concerns across healthcare systems in a PCORnet Clinical Research Network, we used a previously tested rule-based framework tailored to the PCORnet Common Data Model to perform data quality assessment at 13 clinical sites across eight states. Results were compared with the current PCORnet data curation process to explore the differences between both methods. Additional analyses of testosterone therapy prescribing were used to explore clinical care variability and quality. Results: The framework detected discrepancies across sites, revealing evident data quality variability between sites. The detailed requirements encoded the rules captured additional data errors with a specificity that aids in remediation of technical errors compared to the current PCORnet data curation process. Other rules designed to detect logical and clinical inconsistencies may also support clinical care variability and quality programs. Conclusion: Rule-based EHR data quality methods quantify significant discrepancies across all sites. Medication and laboratory sources are causes of data errors.

BackgroundPrevious studies have shown that metabolic syndrome (MetS) is associated with increased systemic inflammation and cardiac mortality in elderly subjects. However, information on the association of inflammation markers with cardiac adverse remodeling is limited in the elderly with MetS. Therefore, we investigated whether the inflammatory marker neutrophil/lymphocyte ratio (NLR) is associated with the cardiac adverse remodeling in Chinese elderly with MetS.MethodsA total of 1,087 hospitalized Chinese elderly (aged ≥ 65 years) with MetS were collected retrospectively. The cross-sectional data of echocardiography and clinical parameters were compared among quartile NLR groups.ResultsIn the elderly with MetS, higher quartile NLR (≥3.83) was found to be associated with male gender, older age, lower estimated glomerular filtration rate (eGFR), and cardiac left ventricular (LV) dilatation (all p

Abstract. Background:. Disease activity indices (DAIs) including disease activity score 28 (DAS28), simplified disease activity index (SDAI), and clinical disease activity index (CDAI) have been widely used in clinical practice and research studies of rheumatoid arthritis (RA). The objective of our study was to evaluate the correlation and concordance among different DAIs in Chinese patients with RA. Methods:. A cross-sectional study, including patients enrolled in the Chinese registry of rheumatoid arthritis from November 2016 to August 2018, was conducted. The correlations were evaluated using Spearman correlation coefficient and concordance with Bland-Altman plots, quadratic weighted kappa, and discordance rates in the crosstab. For other indices, the optimal cutoff points corresponding to SDAI remission were explored through receiver operating characteristic curve analysis. Results:. A total of 30,501 patients were included, of whom 80.46% were women. Most individuals were with moderate disease activity or high disease activity. High correlations among DAS28-erythrocyte sedimentation rate (ESR) and DAS28-C-reactive protein (CRP), SDAI and CDAI were observed. Similarly, the weighted kappa value among the indices was high. In Bland-Altman plots, a positive difference between DAS28-ESR and DAS28-CRP was observed, with an absolute difference of >1.2 in 3079 (10.09%) patients. In crosstab, approximately 30% of the patients were classified into different groups. Concordance values between SDAI remission and the optimal cutoff points of DAS28-ESR, DAS28-CRP, and CDAI were 3.06, 2.37, and 3.20, respectively. Conclusions:. Although DAIs had high correlations and weighted kappa values, the discordance between DAIs was significant in Chinese patients with RA. The four DAIs are not interchangeable.

Abstract There is limited information on the association of body mass index (BMI) with left ventricular (LV) remodeling corresponding to severity of reduced lung function in patients with chronic obstructive pulmonary disease (COPD). Therefore, we investigated whether BMI is associated with cardiac atrial and ventricular dimensions according to severity of lung functional impairment in Chinese COPD elderly. A total of 563 hospitalized COPD patients with lung function impairment and 184 patients with non-COPD (aged 65–92 years) were collected retrospectively in a cross-sectional study in a university affiliated tertiary hospital in China. BMI and cardiac echocardiographic parameters were compared according to severity of lung functional impairment in COPD patients. BMI was 22.9 ± 3.9 kg/m2 in COPD patients, 24.0 ± 4.1 kg/m2 in non-COPD patients respectively. Reduced BMI, LV mass index, LV wall thickness and left atrial diameter, and dilated right ventricle (RV) existed in COPD patients with severe lung dysfunction as compared the COPD patients with mild to moderate lung functional reduction and non-COPD patients (P 0.05). Logistic regression analysis showed that low BMI (BMI

Artificial intelligence (AI) has demonstrated promise in predicting acutekidney injury (AKI), however, clinical adoption of these models requires interpretability and transportability across sites. Here, the authors develop an AKI prediction model and a measure for model transportability across six independent health systems.

Jamming recognition is an essential step in radar detection and anti-jamming in the complex electromagnetic environment. When radars detect an unknown type of jamming that does not occur in the training set, the existing radar jamming recognition algorithms fail to correctly recognize it. However, these algorithms can only recognize this type of jamming as one that already exists in our jamming library. To address this issue, we present two models for radar jamming open set recognition (OSR) that can accurately classify known jamming and distinguish unknown jamming in the case of small samples. The OSR model based on the confidence score can distinguish known jamming from unknown jamming by assessing the reliability of the sample output probability distribution and setting thresholds. Meanwhile, the OSR model based on OpenMax can output the probability of jamming belonging to not only all known classes but also unknown classes. Experimental results show that the two OSR models exhibit high recognition accuracy for known and unknown jamming and play a vital role in sensing complex jamming environments.

Droplet size distribution of dispersed oil in deep-water is critical to the transport and biodegradation of spilled oil in deep-sea. Few studies have focused on the effects of pressure on chemically dispersed oil through experiments. This study thus simulated how the crude oil homogenously pre-dispersed by Corexit 9500A using baffled flasks would behave after being exposed to deep-water conditions. Key factors included dispersant-to-oil ratio (DOR), mixing energy (energy dissipation rate and Kolmogorov microscale), and pressure (up to 150 bar). The variations of pressure were demonstrated to have insignificant effects on the size distribution of pre-dispersed oil. Both the average and medium droplet sizes were correlated negatively with DOR and mixing energy in an established model with a p-value ≤ 0.0011. The log-normal and log-logistic distributions provided a reasonable fit to simulate the droplet size distribution. The two parameters of log-logistic distribution were dependent on DOR and mixing energy with a p-value < 0.005. The results would be valuable to advance the understanding of the behaviours and trajectories of chemically dispersed oil under deep-water conditions. The research helped provide more scientific evidence to improve the understanding of dispersed oil behaviours under high pressure and support deep-sea oil spill research and potential extension of the existing results from shallow water to deep water conditions.

PurposeTo understand what clinical presenting features of sepsis patients are historically associated with rapid treatment involving antibiotics and fluids, as appropriate.DesignThis was a retrospective, observational cohort study using a machine-learning model with an embedded feature selection mechanism (gradient boosting machine).MethodsFor adult patients (age ≥ 18 years) who were admitted through Emergency Department (ED) meeting clinical criteria of severe sepsis from 11/2007 to 05/2018 at an urban tertiary academic medical center, we developed gradient boosting models (GBMs) using a total of 760 original and derived variables, including demographic variables, laboratory values, vital signs, infection diagnosis present on admission, and historical comorbidities. We identified the most impactful factors having strong association with rapid treatment, and further applied the Shapley Additive exPlanation (SHAP) values to examine the marginal effects for each factor.ResultsFor the subgroups with or without fluid bolus treatment component, the models achieved high accuracy of area-under-receiver-operating-curve of 0.91 [95% CI, 0.86-0.95] and 0.84 [95% CI, 0.81-0.86], and sensitivity of 0.81[95% CI, 0.72-0.87] and 0.91 [95% CI, 0.81-0.97], respectively. We identified the 20 most impactful factors associated with rapid treatment for each subgroup. In the non-hypotensive subgroup, initial physiological values were the most impactful to the model, while in the fluid bolus subgroup, value minima and maxima tended to be the most impactful.ConclusionThese machine learning methods identified factors associated with rapid treatment of severe sepsis patients from a large volume of high-dimensional clinical data. The results provide insight into differences in the rapid provision of treatment among patients with sepsis.

Abstract Background Acute kidney injury (AKI), characterized by abrupt deterioration of renal function, is a common clinical event among hospitalized patients and it is associated with high morbidity and mortality. AKI is defined in three stages with stage-3 being the most severe phase which is irreversible. It is important to effectively discover the true risk factors in order to identify high-risk AKI patients and allow better targeting of tailored interventions. However, Stage-3 AKI patients are very rare (only 0.2% of AKI patients) with a large scale of features available in EHR (1917 potential risk features), yielding a scenario unfeasible for any correlation-based feature selection or modeling method. This study aims to discover the key factors and improve the detection of Stage-3 AKI. Methods A causal discovery method (McDSL) is adopted for causal discovery to infer true causal relationship between information buried in EHR (such as medication, diagnosis, laboratory tests, comorbidities and etc.) and Stage-3 AKI risk. The research approach comprised two major phases: data collection, and causal discovery. The first phase is propose to collect the data from HER (includes 358 encounters and 891 risk factors). Finally, McDSL is employed to discover the causal risk factors of Stage-3 AKI, and five well-known machine learning models are built for predicting Stage-3 AKI with 10-fold cross-validation (predictive accuracy were measured by AUC, precision, recall and F-score). Results McDSL is useful for further research of EHR. It is able to discover four causal features, all selected features are medications that are modifiable. The latest research of machine learning is employed to compare the performance of prediction, and the experimental result has verified the selected features are pivotal. Conclusions The features selected by McDSL, which enable us to achieve significant dimension reduction without sacrificing prediction accuracy, suggesting potential clinical use such as helping physicians develop better prevention and treatment strategies.

Background: In the present study, we aimed to investigate the role of epidermal growth factor receptor (EGFR) pathway in the up-regulation of programmed death ligand-1 (PD-L1) caused by radiotherapy (RT). Materials and Methods: Tissue microarrays (TMA) consisting of glioma cancer specimens from 64 patients were used to examine the correlation between PD-L1 and EGFR levels. Furthermore, we performed in vitro experiments to assess the role of EGFR pathway in RT-upregulated PD-L1 expression using human glioma cell lines U87 and U251. Results: Our data demonstrated that the PD-L1 expression was significantly correlated with EGFR expression in glioma specimens (χ2 = 5.00, P = 0.025). The expressions of PD-L1 at the protein and mRNA levels were both significantly up-regulated by RT (P 0.05). The combination of RT with EGFR inhibitor exhibited the same effect on antitumor immune response compared with the combination of RT with PD-L1 neutralizing antibody (Ab). Conclusions: RT could up-regulate the PD-L1 expression through the pathways downstream of EGFR in glioma.

Background/Aims: Several studies have verified the correlation between tumor-infiltrating lymphocytes (TILs) and survival of patients with esophagus cancer (EC). However, the prognostic role of TILs is still controversial. Therefore, we performed this meta-analysis. Methods: We searched PubMed, Embase and the Cochrane Library (last update by August 30, 2017) to identify studies assessing the effect of TILs on survival of patients with EC. Pooled hazard ratios (HRs) for overall survival (OS), disease-free survival (DFS) and cancer specific survival (CSS) were estimated using fixed-effects models or random-effects models, which depends on the heterogeneity. Results: Data from 22 observational studies including 2909 patients were summarized. Pooled analysis indicated that generalized TILs were favorable prognostic markers for OS in patients with EC (pooled HR = 0.48; 95% CI = 0.38-0.61; P < 0.001). For TIL subsets, CD8+ TILs were associated with improved OS (pooled HR = 0.68; 95% CI = 0.58–0.84; P < 0.001) and DFS (pooled HR = 0.90; 95% CI = 0.85-0.95; P < 0.001); FoxP3+ TILs were associated with patients’ DFS (pooled HR = 0.88; 95% CI = 0.81-0.96; P = 0.003). High CD57+ TILs indicated a better OS in patients with EC (pooled HR = 0.50; 95% CI = 0.35-0.72; P < 0.001). In addition, the pooled results showed that other TIL subsets including CD3+, CD4+ and CD45RO+ TILs were not associated with patients’ survival (P > 0.05). Conclusions: For patients with EC, some TIL subsets could serve as prognostic biomarkers. The application of TILs in the immunotherapy of EC needs to be verified through a large amount of clinical research.

Abstract The aim of this study was to investigate the impact of local treatment modalities on the survival of patients with International Federation of Gynecology and Obstetrics (FIGO) stage IB-IIB cervical cancer, including cancer-directed surgery (CDS) alone and CDS combined with radiotherapy (RT). A total of 8,357 patients with cervical cancer between 1988 and 2013 were included in the final study cohort, including 4,298 (51.4%) patients who underwent CDS alone and 4,059 (48.6%) patients who received combination therapy. Univariate and multivariate analyses showed that local treatment modalities were prognostic factors for cause-specific survival (CSS). Patients who received combination therapy had worse CSS (HR = 1.38; 95% CI = 1.20–1.59; P

Background: It has been reported that miR-203 expression was aberrant in various types of cancers, and it could be used as a prognostic biomarker. Therefore, in this study, we aimed to evaluate the prognostic value of miR-203 expression in solid tumors by using meta-analysis and The Cancer Genome Atlas (TCGA) datasets. Methods: By doing a literature research in PubMed, Embase and the Cochrane Library (last update by December 2016), we were able to identify the studies assessing the prognostic role of miR-203 in various tumors. We then used TCGA datasets to validate the results of meta-analysis. Results:33 studies from 26 articles were qualified and enrolled in this meta-analysis. Pooled analyses showed that higher expression of miR-203 in tissues couldn’t predict poor overall survival (OS) and progression-free survival (PFS) in solid tumors. However, the results of subgroup analyses revealed that the upregulation of tissue miR-203 expression was associated with poor OS in colorectal cancer (hazard ratio (HR)=1.81, 95% confidence intervals (CI) 1.31-2.49; P

Well-defined PtNi nanocrystals represent one of the most efficient electrocatalysts to boost the oxygen reduction reaction (ORR), especially in the shape of octahedrons, nanoframes, and nanowires. However, the synthesis of complex PtNi nanostructure is still a great challenge. Herein, we report a new class of PtNi hexapods with high activity and stability toward ORR. The hexapods are prepared by selective capping and simultaneous corrosion. By controlling the oxidative etching, PtNi polyhedrons and nanoparticles are obtained, respectively. The intriguing hexapods are composed of six nanopods with an average length of 12.5 nm. Due to their sharp tips and three-dimensional (3D) accessible surfaces, the PtNi hexapods show a high mass activity of 0.85 A mgPt-1 at 0.9 V vs. RHE, which are 5.4-fold higher than commercial Pt/C, also outperforming PtNi polyhedrons and PtNi nanoparticles. In addition, the mass activity of PtNi hexapods maintains 92.3% even after 10,000 potential cycles.

In the title compound, C19H21NO4, the dihydropyridine ring adopts a distorted screw-boat conformation. The fused cyclohexenone ring forms a slightly distorted envelope conformation. The dihedral angle between the mean planes of the benzene and heterocyclic rings is 86.1 (7)°. An intramolecular C—H...O interaction occurs. In the crystal, molecules are linked by intermolecular N—H...O hydrogen bonds, forming an infinite chain along the c axis.

The molecule of the title compound, C9H8Br2O3, is stabilized by an intramolecular O—H...O interaction. Intermolecular C—H...O interactions connect molecules into a two-dimensional array in the bc plane; connections between these are afforded by π–π stacking interactions [centroid–centroid distance 3.596 (5) Å].

This paper investigates the monotonic limit properties for the minimal and maximal solutions of certain one-dimensional backward stochastic differential equations with continuous coefficients.