Consistency Index Research Articles

Shape stability of a microbubble in a power–law liquid

The onset of non-spherical oscillations of a microbubble in an unbounded power–law liquid, important for biomedical ultrasound applications, is studied. Two sets of evolution equations are obtained from the equation of motion: a Rayleigh Plesset-type equation for the spherical oscillations and an equation for the non-spherical oscillations. The non-spherical oscillations are modeled using the perturbation method via the Legendre polynomials. Two kinds of instabilities, namely parametric and Rayleigh-Taylor instabilities, are investigated. A higher power–law index causes the damping of the oscillations for both spherical and non-spherical oscillations. The power–law index damping effect depends on the ultrasonic drive frequency. At natural frequency, the amplitude of the perturbations is high compared to the non-resonant cases. At a low consistency index, the damping effect of the power–law index decreases. Unlike Newtonian liquids, the viscosity of power–law liquids is affected by the frequency of the acoustic field, thereby affecting Rayleigh-Taylor instability.

Prediction of recurrence-free survival in lung adenocarcinoma based on self-supervised pre-training and multi-task learning

Computed tomography (CT) imaging is a vital tool for the diagnosis and assessment of lung adenocarcinoma, and using CT images to predict the recurrence-free survival (RFS) of lung adenocarcinoma patients post-surgery is of paramount importance in tailoring postoperative treatment plans. Addressing the challenging task of accurate RFS prediction using CT images, this paper introduces an innovative approach based on self-supervised pre-training and multi-task learning. We employed a self-supervised learning strategy known as "image transformation to image restoration" to pretrain a 3D-UNet network on publicly available lung CT datasets to extract generic visual features from lung images. Subsequently, we enhanced the network's feature extraction capability through multi-task learning involving segmentation and classification tasks, guiding the network to extract image features relevant to RFS. Additionally, we designed a multi-scale feature aggregation module to comprehensively amalgamate multi-scale image features, and ultimately predicted the RFS risk score for lung adenocarcinoma with the aid of a feed-forward neural network. The predictive performance of the proposed method was assessed by ten-fold cross-validation. The results showed that the consistency index (C-index) of the proposed method for predicting RFS and the area under curve (AUC) for predicting whether recurrence occurs within three years reached 0.691 ± 0.076 and 0.707 ± 0.082, respectively, and the predictive performance was superior to that of existing methods. This study confirms that the proposed method has the potential of RFS prediction in lung adenocarcinoma patients, which is expected to provide a reliable basis for the development of individualized treatment plans.

Establishment of a prognostic nomogram and discussion on optimal treatment for cervical adenocarcinoma:a retrospective study based on SEER database and Chinese single-center data

Objective: To establish and validate a predicting nomogram for cervical adenocarcinoma based on surveillance, epidemiology and end results (SEER) database and Chinese single-center data, and to explore the optimal treatment for cervical adenocarcinoma. Methods: This study selected 2 478 cervical adenocarcinoma patients from the SEER database as the training cohort, and 195 cervical adenocarcinoma patients from Cancer Hospital of Dalian University of Technology, Liaouing Cancer Hospital and Institute as an external validation cohort. Clinicopathological information and follow-up data of the two cohorts were collected. The radiotherapy group was defined as receiving comprehensive treatment based on concurrent chemoradiotherapy after initial diagnosis, while the surgery group was defined as receiving comprehensive treatment based on radical surgery. Log-rank test and cox regression were used to evaluate factors affecting the prognosis of cervical adenocarcinoma patients. A nomogram was drawn to predict the 3-year and 5-year overall survival rates of cervical adenocarcinoma patients, and then internal validation of the training cohort from SEER database and external validation of the hospital cohort were conducted. Results: (1) In the SEER database training cohort, there were 385 patients (15.54%, 385/2 478) in the radiotherapy group and 2 093 patients (84.46%, 2 093/2 478) in the surgery group. Overall survival time of the radiotherapy group was (55.8±51.3) months, while that of the surgery roup was (94.4±61.7) months, the difference between the two groups was statistically significant (χ2=256.44, P<0.001). Log-rank test showed that age, marital status, maximum of tumor diameters, pathological grade, International Federation of Gynecology and Obstetrics (FIGO) stage, and treatments were all significant factors affecting the overall survival time of cervical adenocarcinoma patients (all P<0.001). Multivariate Cox regression analysis showed that elder (>50 years old), single status, huge tumors (>4 cm), high pathological grades (G2, G3), and advanced FIGO stages (≥Ⅱa2 stage) were independent risk factors for the overall survival time of cervical adenocarcinoma patients (all P<0.05); compared with radiotherapy, surgery was a protective factor for the prognosis of cervical adenocarcinoma patients (HR=0.619, 95%CI: 0.494-0.777; P<0.001). Further analysis of locally advanced stage and Ⅲc stage of patients showed that surgery was a protective factor for the prognosis of cervical adenocarcinoma patients with a maximum tumor diameter >4 to <6 cm (HR=0.414, 95%CI: 0.182-0.942; P=0.036) in locally advanced stage and Ⅲc T1 to T2 stage (HR=0.473, 95%CI: 0.307-0.728; P=0.001). (2) The external validation cohort consisted of 39 patients (20.00%, 39/195) in the radiotherapy group and 156 patients (80.00%, 156/195) in the surgery group. The overall survival time of patients in the radiotherapy group was (51.7±34.3) months, while that of the surgery group was (63.1±26.6) months (χ2=28.41, P<0.001). Further analysis was conducted on locally advanced stage and Ⅲc stage patients, and multivariate Cox regression analysis was performed after propensity score matching, which showed that surgery was a protective factor for the prognosis of cervical adenocarcinoma patients with a maximum tumor diameter >4 to <6 cm in locally advanced stage (HR=0.141, 95%CI: 0.023-0.843; P=0.032) and Ⅲc T1 to T2 stage (HR=0.184, 95%CI: 0.036-0.947; P=0.043). (3) Establishment and internal and external validation of nomogram: based on the six factors screened out by the multivariate Cox regression model, the nomogram was developed to predict the prognosis of cervical adenocarcinoma patients. The consistency index of the internal and external validation were 0.801 and 0.766, respectively, and the calibration curves matched well with the ideal fitting line. Conclusions: The key to the treatment of cervical adenocarcinoma is to prioritize radical surgery for patients with conditions for radical tumor resection. Compared with concurrent chemoradiotherapy, patients with locally advanced stages (Ⅰb3, Ⅱa2), and Ⅲc (T1, T2) stages cervical adenocarcinoma could benefit from comprehensive treatment based on radical surgery. The nomogram of this study has been validated internally and externally, and show good survival prediction efficacy for cervical adenocarcinoma patients.

Effect of fucoidan on rheological properties of xanthan gum-guar gum mixtures

The goal of this study is to investigate the effect of fucoidan on the rheological properties of xanthan gum (XG)-guar gum (GG) mixtures with mixing XG/GG ratios of 75/25 or 50/50. All mixtures showed shear-thinning behavior. The consistency index (K) and apparent viscosity at 50 s−1 (ηa,50) values of the mixtures with 0.5% fucoidan were higher than those of mixtures without it, indicating synergistic interactions among the three gums. A more pronounced change in activation energy for ηa,50 was observed in the XG50/GG50 mixture with increasing fucoidan concentration. The tan δ values of the mixtures increased as the fucoidan concentration was increased. Regardless of the fucoidan concentration, the relative K and viscoelastic moduli values of the mixtures were higher than 1.0. Although the XG50/GG50 mixture showed higher relative K, ηa,50, and viscoelastic moduli values than the XG75/GG25 mixture, the gaps between the relative values of the mixtures decreased with increasing fucoidan concentration. Thus, the results demonstrate that there was stronger rheological synergism in the XG50/GG50 mixtures than in the XG75/GG50 mixtures with a low fucoidan concentration (<1.0%) and that the rheological synergism was affected by the level of fucoidan content. Our findings demonstrate that rheological properties of XG-GG mixtures were influenced by fucoidan content. This may prompt further studies on the rheological characteristics of fucoidan-based mixture system, facilitating the widespread application of fucoidan in the food industry.

GEOTECHNICAL AND MINERALOGICAL CHARACTERISTICS OF LATERITIC SOIL AND LOCUST BEAN (PARKIA BIGLOBOSA) PODS ASH AS CONSTRUCTION SOIL

African locust bean (Parkia Biglobosa) has been in great demand and consequently yielding large amounts of the pods which could be a potential hazard to the environment. Converting the pods to ash that would be utilized as construction material is another way of handling them properly. The effects of the mineralogy of the soil on its geotechnical characteristics when the soil is treated with locust bean pod ash have been given very little attention. Therefore, this study considered the effects of locust bean pod ash (LBPA) and the mineralogy of lateritic soil on some geotechnical properties necessary for it to be used as subgrade or foundation soil. The determination of the chemical constituents of the LBPA was carried out using Atomic Absorption Spectrometer. The lateritic soil was characterized by identifying the clay minerals as well as non-clay minerals present in the soil using the x-ray diffraction technique and preliminary tests were also carried out to properly rate the soil. The soil was treated by applying dosages of LBPA 0 – 25% at intervals of 5% and the percentages were measured by weight of the dry soil. The tests conducted on the prepared soil samples with LBPA were specific gravity, consistency indices, compaction (British Standard Light), California bearing ratio and direct shear box test. The LBPA was found to be an acceptable pozzolanic material for the treatment of the lateritic soil. The lateritic soil was observed to belong to soil groups A-2-6(0) in the AASHTO and poorly graded sand (SP) in USCS ratings. It was also observed that the non-clay minerals present in the soil were quartz, feldspar and mica whereas the clay minerals present were kaolinite, iolite, vermiculite and chlorite which had a significant influence on the geotechnical characteristics of the soil. The specific gravity of the LBPA was relatively low and the additions of LBPA reduced the specific gravity of the soil. The consistency indices also dropped and subsequently increased with the further addition of LBPA. The increase in LBPA contents caused increments in the optimum moisture content while the maximum dry density and shear strength parameters reduced. The strength characteristics like the California Bearing Ratio of the lateritic soil improved by 173.91% at the addition of 5% LBSA content which was determined to be the optimum dosage.

UTILIZATION OF HAZELNUT SKIN AND HAZELNUT FLOUR IN GLUTEN-FREE CAKES: CORRELATION OF BATTER RHEOLOGY WITH CAKE QUALITY

The effects of rice flour substitution with hazelnut skin (HS), hazelnut flour (HF), and HS-HF blend (1:1, w/w) at percentages of 0%, 5%, 10%, 15% (w/w) on gluten-free cake batters were studied from a rheological standpoint. Replacement with 5% HS increased Power-Law consistency index (K), reduced specific gravity and resulted in the highest cake volume. Increasing levels of HS gradually increased specific gravity, water activity, and reduced tan, leading to cakes with lower volume, darker (lower L*) color, harder texture. HF addition increased tan (at &amp;gt;5%) and specific gravity, producing cakes with lower volume, but similar color and texture to those of control. HS-HF blend improved cake color and hardness compared to HS added alone. Strong correlations were found between G() slope and cake volume (r=0.9939 for added HS, r=-0.9408 for added HF), the exponent a and cake volume (r=0.9447 for added HS, r=-0.8668 for added HF).

Properties experimental investigation of water-based drilling mud contained tragacanth gum and synthesized zinc oxide nanoparticles

Drilling fluids play crucial role in the oil and gas production industry, consequently the optimization of flow behavior of these fluids has received remarkable attention from the beginning of this process. The objective of this study is to improve the rheological and filtration characteristics of water-based mud (WBM) by incorporating zinc oxide (ZnO) nanoparticles (NPs) and affordable tragacanth gum (TG) polymer. Initially, ZnO NPs were synthesized through a facile and straightforward sol–gel method and subjected to comprehensive characterization. Subsequently, these NPs were incorporated into TG polymer solutions to formulate drilling mud samples. The selection of optimal samples involved meticulously determining of ZnO NPs and TG polymer concentrations as influential parameters facilitated by the Design Expert software. The responses taken into consideration in this methodology included flow behavior index (n), consistency index (K), plastic viscosity (PV), and yield point (YP). The investigating rheological parameters entailed utilizing both the Power-law and Bingham-plastic models, underscoring the scholarly refinement of the study’s analytical approach. Subsequently, an analysis of variance (ANOVA) was conducted to assess the significance of the model and its parameters. Three optimal samples were carefully selected based on the results obtained from the modeling and analysis of the rheological parameters. The next phase involved utilizing these optimal samples to investigate their filtration properties in detail. The final step led to selecting the optimal sample composition, which was determined to be 0.25 wt% ZnO NPs and 750 ppm TG polymer based on the optimization results provided by the Design Expert software. Remarkably, this specific combination yielded significant improvements in PV (22.2 %), YP (109.5 %), mud cake thickness (20 %), and fluid loss (2.87 %). Moreover, the resulting mud exhibited desirable rheological properties, including a K of 31.20 (cp) and an n of 0.21. This specific combination was identified as the most favorable composition for achieving the desired rheological and filtration properties.

An [formula omitted]-cut intervals based Fuzzy Best–Worst Method for Multi-Criteria Decision-Making

To address ambiguity arising from linguistic decision judgments, Guo and Zhao introduced a model of the well-known Multi-Criteria Decision-Making (MCDM) method, Best-Worst Method (BWM), using fuzzy sets, known as Fuzzy Best–Worst Method (FBWM). Despite its versatility, FBWM has limitations, such as criteria-weights being independent of fuzzy comparison values’ shape and reliance on approximate fuzzy arithmetic operations. In response to these limitations, we introduce a novel model of Fuzzy Best–Worst Method based on α-cut intervals. In this model, the calculation of optimal weights involves formulating an optimization problem that utilizes exact fuzzy arithmetic operations defined in terms of α-cut intervals. This approach aims to optimize the entire shape of fuzzy comparison values simultaneously. However, it turns out that, although we have proven the existence of optimal solution for this problem, solving it proves to be challenging. To resolve this issue, we approximate optimal weight set(s) using triangular fuzzy weight sets and assess the Error of Approximation (EA). The approximate weight set with the desired EA is then defuzzified to obtain a crisp weight set. In situations where there are multiple approximate weight sets with the same EA, interval-weights are calculated. Following that, we establish the necessary conditions for a Fuzzy Pairwise Comparison System (FPCS) to be consistent. Using these conditions, we calculate a lower bound of the Consistency Index (CI), providing a measure of the accuracy of weights. Finally, we discuss numerical examples and a real-world scenario, ranking of risk factors in supply chain 4.0, to validate the effectiveness of the proposed model.

Specific mortality in patients with diffuse large B-cell lymphoma: a retrospective analysis based on the surveillance, epidemiology, and end results database.

The full potential of competing risk modeling approaches in the context of diffuse large B-cell lymphoma (DLBCL) patients has yet to be fully harnessed. This study aims to address this gap by developing a sophisticated competing risk model specifically designed to predict specific mortality in DLBCL patients. We extracted DLBCL patients' data from the SEER (Surveillance, Epidemiology, and End Results) database. To identify relevant variables, we conducted a two-step screening process using univariate and multivariate Fine and Gray regression analyses. Subsequently, a nomogram was constructed based on the results. The model's consistency index (C-index) was calculated to assess its performance. Additionally, calibration curves and receiver operator characteristic (ROC) curves were generated to validate the model's effectiveness. This study enrolled a total of 24,402 patients. The feature selection analysis identified 13 variables that were statistically significant and therefore included in the model. The model validation results demonstrated that the area under the receiver operating characteristic (ROC) curve (AUC) for predicting 6-month, 1-year, and 3-year DLBCL-specific mortality was 0.748, 0.718, and 0.698, respectively, in the training cohort. In the validation cohort, the AUC values were 0.747, 0.721, and 0.697. The calibration curves indicated good consistency between the training and validation cohorts. The most significant predictor of DLBCL-specific mortality is the age of the patient, followed by the Ann Arbor stage and the administration of chemotherapy. This predictive model has the potential to facilitate the identification of high-risk DLBCL patients by clinicians, ultimately leading to improved prognosis.

Evaluation of the technological and compositional features of pancakes fortified with Acheta domesticus

This work focused on the nutritional and technological evaluation of pancakes fortified with increasing Acheta domesticus powder (AP) levels. Scientific literature underscores AP's potential as an ingredient in bakery formulations due to its notable fiber and protein content. Thus, we formulated different pancake samples by replacing wheat flour (WF) with 10, 20, and 30% of AP, denoted as AP10, AF 20, and AP30, respectively, alongside a control sample (CP). We evaluated Water Absorption Capacity (WAC) and Water Solubility Index (WSI) on WF, AP, different WF and AP mixes, and batters' rheology. Lastly, we assessed the pancakes' physical, technological, and compositional parameters. The consistency index, flow index, and density increased from CP to AP30. A similar trend was observed for the textural parameter of hardness and chewiness, while cohesiveness slightly decreased. The pancake diameter and height were higher in fortified samples than in CP. A noticeable shift from brighter to darker color was observed from CP to AP30, with an increase in the a* (toward red) and b* parameters (toward blue). AP can represent a valuable ingredient for baked good fortification.

Analysis of risk factors associated with diffuse alveolar haemorrhage in patients with ANCA-associated vasculitis and construction of a risk prediction model using line graph.

This study aims to analyse the risk factors associated with diffuse alveolar haemorrhage (DAH) in patients with ANCA-associated vasculitis (AAV) and construct a risk prediction model using line graph. A retrospective study was conducted from January 2012 to May 2023 at the First Clinical College of Three Gorges University, focusing on patients diagnosed with AAV. Clinical and laboratory data were collected from these patients. The potential predictors subsets of high-risk AAV combined with DAH were screened by LASSO regression and 10-fold cross-validation method, and determined by using multivariate Logistic regression analysis, then were used for developing a prediction nomogram for high-risk AAV combined with DAH using the R software. ROC curve analysis was used to validate the model's stability. Internal validation was performed using a bootstrap method. The discrimination of the nomogram was determined by calculating the average consistency index(C-index). The calibration curve was used to assess the calibration of the nomogram. A total of 234 patients with AAV were included, among whom 85 developed DAH, with an incidence rate of 36%, and the average age was 63±12. Multivariable logistic regression analysis showed that Age [OR=1.037 (95%CI: 1.006, 1.071), p=0.019], platelet count (PLT) [OR=0.996 (95%CI: 0.992, 0.999), p=0.029], ESR [OR=1.028 (95%CI: 1.015, 1.042), p<0.01], HB [OR=0.978 (95%CI: 0.959, 0.996), p=0.024], and haematuria [OR=3.77 (95%CI: 1.677, 8.976), p=0.001] were found to be independent predictors of AAV combined with DAH and were used to construct a nomogram. The AUCROC values of the nomogram for DAH in AAV patients was 0.852 (95%CI: 0.801, 0.903), and the C-index could reach 0.824 after internal verification, showing good differentiation and consistency. The new nomogram, which included age, Hb, ESR, PLT and haematuria as variables, had the potential to predict the risk of AAV patients complicated with DAH.

Prognostic predictive value of urothelial carcinoma of the bladder after TURBT based on multiphase CT radiomics.

To investigate multiphase computed tomography (CT) radiomics-based combined with clinical factors to predict overall survival (OS) in patients with bladder urothelial carcinoma (BLCA) who underwent transurethral resection of bladder tumor (TURBT). Data were retrospectively collected from 114 patients with primary BLCA from February 2016 to February 2018. The regions of interest (ROIs) of the plain, arterial, and venous phase images were manually segmented. The Cox regression algorithm was used to establish 3 basic models for the plain phase (PP), arterial phase (AP), and venous phase (VP) and 2 combination models (AP + VP and PP + AP + VP). The highest-performing radiomics model was selected to calculate the radiomics score (Rad-score), and independent risk factors affecting patients' OS were analyzed using Cox regression. The Rad-score and clinical risk factors were combined to construct a joint model and draw a visualized nomogram. The combined model of PP + AP + VP showed the best performance with the Akaike Information Criterion (AIC) and Consistency Index (C-index) in the test group of 130.48 and 0.779, respectively. A combined model constructed with two independent risk factors (age and Ki-67 expression status) in combination with the Rad-score outperformed the radiomics model alone; AIC and C-index in the test group were 115.74 and 0.840, respectively. The calibration curves showed good agreement between the predicted probabilities of the joint model and the actual (p < 0.05). The decision curve showed that the joint model had good clinical application value within a large range of threshold probabilities. This new model can be used to predict the OS of patients with BLCA who underwent TURBT.

3D-Animated Cartoon Instructional Package and Effective Teaching of Selected Topics in Financial Accounting in Pubic Secondary Schools, South-South, Nigeria

This study was carried out to determine the difference in students’ academic performance in financial accounting when taught using 3D-cartoon animation package and a conventional approach. The selected topics for the study include transaction analysis, accounting equation, cash book and ledger. The research design the researchers adopted for this study was quasi quasi-experimental method and the area of the study was South-South, Nigeria. The population of the study consisted of 242,052. The sample size was 192 and a purposive sampling technique was used for the study. The Financial Accounting Achievement Test (FAAT) was used to collect data for the study. The internal consistency index of .92 was obtained using test-retest. The data were analyzed using mean and standard deviation to answer research questions and ANCOVA to test the null hypotheses at .05 level of significance. Among other recommendations made was that the government should encourage schools to embrace the latest teaching strategies by way of providing the 3D instructional package for use in schools.

Promoting Sustainable Development in Urban–Rural Areas: A New Approach for Evaluating the Policies of Characteristic Towns in China

The Sustainable Development Goals, adopted by all United Nations Member States, emphasize sustainable cities and communities, aiming to strengthen development planning and foster positive links between urban and rural areas by 2030. As the newly leading platform for urbanization development, characteristic towns (‘Tese Xiaozhen’ in Chinese) contribute to the target of sustainable urbanisation, wherein town policies are especially important for leading the sound development of characteristic towns. However, the effect of these characteristic towns policies remains uncertain. Additionally, most related studies have utilized qualitative methodologies in policy evaluation, which may be inadequate to guide actual practice. Thus, in order to accurately acknowledge the effect of characteristic towns policies, a policy evaluation framework is established in this paper, utilising the multiple streams theory, text mining and the Policy Modelling Consistency Index model (PMC-Index model). Then, taking 225 policy documents promulgated in China from 2015 to 2022 as the research objects, policy evaluation indicators were selected by combining the multiple streams theory to improve the PMC-Index model and a text mining method. Thereafter, an empirical analysis was conducted to evaluate the consistency of 10 characteristic towns policies chosen. The results indicate that the mean value of the PMC indexes of the 10 examined policies is 7.13 in the total of 9 points, which means that the general performance of the characteristic town policies is satisfactory, yet the low scores in terms of effectiveness, content, and guarantee. In the end, some recommendations and suggestions are proposed for clarifying administrative attributes, optimizing the integration of urban and rural resources, and adjusting the policy hierarchy to a bottom-up approach. This study not only provides a policy evaluation framework to comprehensively understand the consistency of global urbanization policies but also offers a beneficial reference for promote urban–rural sustainable development.

Mechanism of microRNA regulating apoptosis after reperfusion in patients with mechanical thrombectomy.

Stroke is the second leading cause of death worldwide. Understanding of gene expression dynamics could bring new approaches in diagnostics and therapy of stroke. Small noncoding molecules termed 'microRNA' represent the most flexible network of gene expression regulators. To screen out miRNAs that are mainly regulated during reperfusion in mechanically embolized patients, and study their mechanisms of action in reperfusion injury after thrombectomy, in order to find new therapeutic targets for mechanically embolized patients. Serums from 30 patients with moderate to severe stroke after mechanical thrombectomy (MT) were collected to measure miRNA expressions. Clinical information of patients was analyze, and patients were divided into poor prognosis and good prognosis. Factors affecting prognosis was classified, and independent risk factors for poor prognosis were determined. Prognostic value of National Institutes of Health Stroke Scale (NIHSS) score on admission to patients with MT was assessed. ROC (receiver operating characteristic) curves were drawn, and Kaplan-Merier method determined whether different NIHSS scores at admission had any difference in the in-hospital survival rate of consistency index/random consistency index (CI/RI) patients treated with MT. An oxygen-glucose deprivation/reperfusion (OGD/R) cell model and an middle cerebral artery occlusion (MCAO)/reperfusion mouse model were established, in which miR-298 expression was tested. In OGD/R cells, proliferation, apoptosis, and autophagy were assessed after intervention with miR-298 and/or autophagy related gene 5 (ATG5). In MCAO mice, the infarct area was calculated, and neurological function was assessed. The relationship between miR-298 and ATG5 was explored and validated. Age, diabetes, hypertension, hemorrhage transformation, NIHSS score at admission, leukocyte, neutrophil count and neutrophil to lymphocyte ratio (NLR) level were associated with patient's prognosis. Diabetes, NIHSS score at admission, and hemorrhagic transformation were independent risk factors for predicting poor prognosis in patients treated with MT. NIHSS score on admission had a predictive value on patient's prognosis. miR-298 was upregulated in acute cerebral ischemia patients with MT (p<0.05), especially in those with poor prognosis. miR-298 was elevated in both cell and mouse models (p<0.05). Apoptosis and autophagy of cells were weakened after miR-298 knockdown, and infarction in the mouse brain tissues was reduced. ATG5 was a target of miR-298. Overexpressing ATG5 rescued miR-298-induced apoptosis and autophagy. In conclusion: regulation of miR-298 and ATG5 attenuates neuronal apoptosis and autophagy, providing a new strategy for brain injury after reperfusion in patients with MT.

Identification of immune-related prognostic biomarkers in triple-negative breast cancer.

Triple-negative breast cancer (TNBC), a type of breast cancer, lacks immune-related markers that can be used for prognosis or prediction. Therefore, we created a predictive framework for TNBC using a risk assessment. Our previous study group consisted of 360 individuals who were diagnosed with TNBC through pathology using RNA sequencing and had clinical data from Fudan University Shanghai Cancer Center (FUSCC). A risk scoring model was constructed using the Cox regression method with the least absolute shrinkage and selection operator (LASSO). A multivariate Cox regression analysis was utilized to develop the prediction model, which was then assessed using the consistency index and calibration plots. The validation cohort of The Cancer Genome Atlas (TCGA) TNBC confirmed the strength of the signatures' predictive value. The prognostic risk score model included 12 genes: TDO2, CHIT1, CARML2, HLA-C, ADIRF, C19orf33, CA8, AHNAK2, RHOV, OPLAH, THEM6, and NEBL. The receiver operator characteristic (ROC) curves for survivability values at 1, 3, and 5 years in the FUSCC TNBC cohort demonstrated area under the curve (AUC) values of 0.78, 0.83, and 0.75, respectively. These results indicated a high level of accuracy in predicting outcomes, which was further confirmed through validation using TCGA database. The patients in the high-risk group showed worse prognoses and lower levels of immune cell infiltration, specifically CD8+ T cells, than those in the low-risk group. Furthermore, the low-risk group exhibited a significant upregulation of genes that encode immune checkpoints, including CD274 and CTLA4, suggesting that immunotherapy may yield enhanced efficacy within this particular group. In conclusion, the prognostic signature consisting of 12 genes can assist in the choice of immunotherapy for TNBC.

A comparative study on the rheological properties of concentrated xanthan gum in combination with gum arabic or gum arabic-based emulsion

A goal of this study is to explore the difference in rheological properties of xanthan gum (XG)-based mixtures with gum arabic (GA) or GA-based emulsion (GAE). The stability of GAE was improved by thickening with XG. The intrinsic viscosity of all mixtures decreased as GA concentration increased, implying an XG conformational transition from the disordered to the ordered form. All mixtures except for an XG-GA mixture at 6.0 % GA attained a higher consistency index value than XG alone, indicating synergistic interactions between the components. At a high GA concentration (>3.0 %), the XG-GAE mixture showed higher relative apparent viscosity values than the XG-GA mixture. All mixtures except for an XG-GA mixture at 6.0 % GA showed higher elastic modulus and lower viscous modulus values than XG alone. Consequently, all mixtures showed lower tan δ values (0.26–0.30) than XG alone (0.31). Moreover, with a high GA concentration (>1.5 %), the XG-GAE mixtures achieved lower relative tan δ values than XG-GA mixture. These results indicate that XG formed a higher weak gel-like network with GAE than GA. Overall, the findings demonstrate that the interaction between XG and GA is influenced by conformational changes in the latter in both aqueous and emulsion systems.

Non-encapsulated, encapsulated, and lyophilized probiotic Limosilactobacillus reuteri SW23 influenced the growth and gut health in calves

The present study was conducted to assess the impact of non-encapsulated, air-dried microencapsulated, and lyophilized microencapsulated probiotics in indigenous cattle calves (Bos indicus). Twenty-four (5–7 days old) indigenous cattle calves were selected and assigned into four groups, with six calves in each as follows: control (CON), fed milk and basal diet alone, and treatment groups supplemented with non-encapsulated (NEC), air-dried microencapsulated (AEC) and lyophilized microencapsulated (LEC) probiotic L. reuteri SW23 at 108 CFU/head/day in skim milk as a carrier provided for 60 days. The animals were divided into four groups, adopting a complete randomized design, and the effects were considered significant at p ≤ 0.05. Probiotics supplementation increased (p < 0.05) body weight gain (kg), average daily gain, and structural growth measurements in calves of all treatment groups. Dry matter intake (g/d), feed conversion efficiency, and fecal counts of Lactobacilli and Bifidobacteria were also increased in the treatment groups compared to CON. The fecal consistency index was highest in CON (0.70 ± 0.03), followed by NEC (0.68 ± 0.01), AEC (0.66 ± 0.02), and LEC (0.65 ± 0.02). Fecal pH and ammonia levels were reduced (p < 0.05) in the probiotic-fed groups compared to CON, with a concomitant increase in fecal lactate, acetate, and propionate levels. In addition, cell-mediated and humoral immunity were significantly increased in supplemented groups as compared to CON. Thus, it can be concluded that supplementation of the probiotics in microencapsulated/non-encapsulated forms to neonatal calves had a variety of positive effects on their health, including better performance, improved gut health, and a lower fecal consistency index. Moreover, among all supplemented groups, the lyophilized microencapsulated group outperformed air-dried microencapsulated and non-microencapsulated groups in terms of ADG, DMI, and gut health.

Risk factors and a nomogram for predicting local recurrence in adult patients with early gastric cancer after endoscopic submucosal dissection

Background and aimsEndoscopic submucosal dissection (ESD) is an effective treatment method for early gastric cancers. The aim of this study was to evaluate the risk factors of recurrence for patients with early gastric cancer after ESD and construct a nomogram for predicting recurrence. MethodsA retrospective observational study was conducted on patients with early gastric cancer who underwent ESD at Beijing Friendship Hospital between 2013 and 2018. The risk factors of gastric cancer recurrence after ESD were analyzed by univariate and multivariate Cox regression. ResultsA total of 238 patients with a median follow-up period of 70.5-month were enrolled in the study. Risk factors for recurrence included diabetes (HR = 3.68), alcohol consumption history (HR = 5.73), complications (HR = 5.22), lymphatic invasion (HR = 13.09) and multiple lesions (HR = 4.34). The analysis of the receiver operating characteristic curve, calibration curve, and model consistency index demonstrates that the graphical representation exhibits a good predictive capability. ConclusionsBased on identified risk factors, this study developed the first nomogram with high accuracy to predict the recurrence of early gastric cancer after ESD. This model offers valuable guidance to clinicians for identifying high-risk patient groups and planning more intensive follow-up strategies.

A Retrospective Study of Biological Risk Factors Associated with Primary Knee Osteoarthritis and the Development of a Nomogram Model.

A high percentage of the elderly suffer from knee osteoarthritis (KOA), which imposes a certain economic burden on them and on society as a whole. The purpose of this study is to examine the risk of KOA and to develop a KOA nomogram model that can timely intervene in this disease to decrease patient psychological burdens. Data was collected from patients with KOA and without KOA at our hospital from February 2021 to February 2023. Initially, a comparison was conducted between the variables, identifying statistical differences between the two groups. Subsequently, the risk of KOA was evaluated using the Least Absolute Shrinkage and Selection Operator method and multivariate logistic regression to determine the most effective predictive index and develop a prediction model. The examination of the disease risk prediction model in KOA includes the corresponding nomogram, which encompasses various potential predictors. The assessment of disease risk entails the application of various metrics, including the consistency index (C index), the area under the curve (AUC) of the receiver operating characteristic curve, the calibration chart, the GiViTi calibration band, and the model for predicting KOA. Furthermore, the potential clinical significance of the model is explored through decision curve analysis (DCA) and clinical influence curve analysis. The study included a total of 582 patients, consisting of 392 patients with KOA and 190 patients without KOA. The nomogram utilized age, haematocrit, platelet count, apolipoprotein a1, potassium, magnesium, hydroxybutyrate dehydrogenase, creatine kinase, and estimated glomerular filtration rate as predictors. The C index, AUC, calibration plot, Giviti calibration band, DCA and clinical influence KOA indicated the ability of nomogram model to differentiate KOA. Using nomogram based on disease risk, high-risk KOA can be identified directly without imaging.