Testing and Validating Instruments for Feedstocks of Mineral Carbonation

Different feedstocks Dunite, Olivine and Lizardite are examined in this research using various measuring techniques such as TGA-MS, XRD and Quantitative XRD and EDS. Quantitative XRD results matched with TGA-MS results. Malvern Mastersizer, EDS and QXRD results also showed a good match regarding the individuality of results which are shown graphically. TGA-MS calibration curves example is provided. Matching the results of different measuring techniques is a key to fundamental research. Comparison of the reactivity of dunite, soaked dunite, heat-activated dunite and lizardite and raw dunite soaked has been performed. TGA-MS and QXRD results match each other. Malvern Mastersizer, EDS and QXRD results match with their individual results indicating the instrument’s reliability. Semi-Quantitative XRD results authenticity is EXCELLENT. TGA-MS results match with QXRD is excellent. Mineral carbonation converts CO2 into stable mineral carbonates. This research explores the utilisation of serpentinised dunite (which is comprised of 61% lizardite) as a potential feedstock for mineral carbonation. Heat activation, ex-situ regrinding and concurrent grinding techniques were employed to enhance the reaction rate and yield, and to provide information on the carbonation reaction mechanism. Silica-rich layers that appeared during reference experiments were disrupted using concurrent grinding and significantly higher magnesite yields and Mg extractions were obtained.

Nomogram for Predicting Overall Survival in Patients With Invasive Micropapillary Carcinoma After Breast-Conserving Surgery: A Population‐Based Analysis

Background: Due to the rarity of invasive micropapillary carcinoma (IMPC) of the breast, no randomized trial has investigated the prediction of overall survival (OS) for patients with IMPC after breast-conserving surgery (BCS). This study aimed to construct a nomogram for predicting OS in IMPC patients after BCS. Methods: Using the Surveillance, Epidemiology, and End Results (SEER) database, 481 eligible cases diagnosed with IMPC were collected. OS in IMPC patients after BCS were assessed through multivariable Cox analyses, Harrell’s concordance indexes (C-indexes), receiver operating characteristics (ROCs) curves, calibration curves, decision curve analyses (DCA), and survival analyses. Results: 336 patients were randomly assigned into training cohort and 145 cases in validation cohort. The multivariate Cox regression analyses revealed that age at diagnosis, American Joint Committee on Cancer (AJCC) stage, marital status, hormone receptor status and chemotherapy were significant prognostic factors for OS in conservatively operated IMPC patients. The nomogram had a good prediction performance with the C-indices 0.771 (95%CI, 0.712-0.830) and 0.715 (95%CI, 0.603-0.827) in training and validation cohorts, respectively, and good consistency between the predicted and observed probability, with calibration curves plotted and the slope was close to 1. Based on calculation of the model, participants in low-risk group had a better OS in comparison with those in high-risk group (P < 0.001). Conclusions: A nomogram was developed to predict individualized risk of OS for IMPC patients after BCS. By risk stratification, this model is expected to guide treatment decision making in improving long-term follow-up strategies for IMPC patients.

Estimation of Quercetin and Rutin Content in Hyouttunia cordata and Centella asiatica Plant Extracts Using UV-Spectrophotometer

Flavonoids are secondary plant metabolites normally found as pigmented compounds in plants. Quercetin and rutin are two important and commonly found flavonoids in nature and exhibit wide pharmacological effects such as antioxidant, anticarcinogenic, antiviral, anti-inflammatory, antidiabetic, and hepatoprotective activities as well as antimicrobial activity. In this study, quercetin and rutin content is being quantified in the plant extracts of Centella asiatica and Houttuynia cordata and considerable amounts of these two flavonoids were depicted. A single beam UV – Spectrophotometer was used to measure the absorbance of the standard as well as test solutions. Calibration curves were constructed for standard quercetin and rutin in such a way that x-axis denotes concentration and the y-axis denotes the absorbance. The calibration curves showed linearity at concentrations 5-25 ?g /ml of quercetin and rutin respectively with a good correlation coefficient (r) of 0.99 for both the curves. The absorbance of the two test extracts was obtained from the calibration curve and respective concentrations of quercetin and rutin for the two extracts were calculated. The amount of quercetin and rutin present was expressed as Total Flavonoid Content (TFC) i.e. the amount of the flavonoid in ?g present per mg of the respective plant extract. The quercetin content in both the plant extracts was found to be more (315.8 in Houttuynia cordata; 487.6 in Centella asiatica) than the content of rutin (152.2 in Houttuynia cordata; 171.0 in Centella asiatica).

A Smartphone-Based Detection Method of Colloidal Gold Immunochromatographic Strip

The outbreak of the new coronavirus (SARS-CoV-2) infection has become a global public health crisis. Antigen detection strips (colloidal gold) can be widely used in novel coronavirus clinical screening and can even be extended to home self-testing, which provides a practical and effective way for people to obtain health status information away from the crowd. In this paper, a colloidal gold detection system without complex devices is proposed, which is based on smartphone usage along with a mobile-phone software embedded with normalization algorithms and a special designed background paper. The basic principle of the device relies on image processing. First, the data of the green channel of the image captured by a smartphone are selected to be processed. Second, the calibration curves are established using standard black and white card, and the calibration values under different detection environments are obtained by calibration curves. Finally, to verify the validity of the proposed method, various standard solutions with different concentrations are tested. Results show that this method can eliminate the influence of different environments on the test results, the test results in different detection environments have good stability and the variation coefficients are less than 5%. It fully proves that the detection system designed in this paper can detect the result of colloidal gold immunochromatographic strip in time, conveniently and accurately in different environments.

A Novel Nomogram for Predicting Gestational Diabetes Mellitus During Early Pregnancy

ObjectiveGestational diabetes mellitus (GDM) is a serious threat to maternal and child health. However, there isn’t a standard predictive model for the disorder in early pregnancy. This study is to investigate the association of blood indexes with GDM and establishes a practical predictive model in early pregnancy for GDM.MethodsThis is a prospective cohort study enrolling 413 pregnant women in the department of Obstetrics and Gynecology in Shanghai General Hospital from July 2020 to April 2021.A total of 116pregnantwomen were diagnosed with GDM during the follow-up. Blood samples were collected at early trimester (gestational weeks 12-16) and second trimester(gestational weeks 24-26 weeks). A predictive nomogram was established based on results of the multivariate logistic model and 5-fold cross validation. We evaluate the nomogram by the area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCAs).ResultsSignificant differences were observed between the GDM and normal controls among age, pre-pregnancy BMI, whether the pregnant women with complications, the percentage of B lymphocytes, fasting plasma glucose (FPG), HbA1c, triglyceride and the level of progesterone in early trimester. Risk factors used in nomogram included age, pre-pregnancy BMI, FPG, HbA1c, the level of IgA, the level of triglyceride, the percentage of B lymphocytes, the level of progesterone and TPOAb in early pregnancy. The AUC value was 0.772, 95%CI (0.602,0.942). The calibration curves for the probability of GDM demonstrated acceptable agreement between the predicted outcomes by the nomogram and the observed values. DCA curves showed good positive net benefits in the predictive model.ConclusionsA novel predictive nomogram was developed for GDM in our study, which could do help to patient counseling and management during early pregnancy in clinical practice.

Development and validation of postoperative predictive recurrence nomograms in patients with persistent atrial fibrillation: a retrospective cohort study

Background： Patients with persistent atrial fibrillation（PsAF） still have a higher risk of recurrence after catheter radiofrequency ablation. Nevertheless, effective recurrence forecast tools have not been established for these patients. Thus, this research aimed to develop and validate an easy-to-use linear prediction model for predicting postoperative recurrence in patients with PsAF. Methods： We conducted a single-center, retrospective, observational study of patients with PsAF admitted to our hospital from June 2013 to June 2021. Univariate analysis was used to screen risk factors, then we used multivariate regression analysis to evaluate the independence of each risk factor and construct a combined prediction model which incorporated into a nomogram, finally, we took the receiver operating characteristic (ROC) curve to predict the value of nomogram model. Additionally, the calibration curves and decision curve analysis (DCA) were also performed to assess the clinical utility of the nomogram. Results： A total of 209 subjects were included in the study and 42 (20.10%) were followed up to September 2021 for recurrent AF. Duration of AF, Left atrial diameter(LAD), BMI, CKMB, and alcohol consumption were independent risk factors (P < 0.05), these variables were integrated into the nomogram model, and the area under the curve （AUC） was 0.895, the sensitivity was 93.3%, and the specificity was 71.4%, indicating that the model had an excellent predictive performance. The C-index of the predictive nomogram model was 0.906. The calibration curves and DCA results manifested that the Model had a splendid predictive correction and discrimination ability. Conclusion： This simple and innovative clinical nomogram (that any clinician can use in the daily clinic) can help evaluate the risk of recurrence after catheter ablation in PsAF, facilitate preoperative evaluation as well as the postoperative follow-up, and may also help generate personalized therapeutic strategies.

Overall and cancer-specific survival in patients with breast Paget disease: A population-based study

Paget disease of the breast is an uncommon malignant tumor with an inferior outcome. Therefore, establishing nomograms to predict the survival outcomes of breast Paget disease patients is urgent. Clinicopathological and follow-up data of breast Paget disease patients diagnosed between 2010 and 2016 were retrieved through the Surveillance, Epidemiology, and End Result (SEER) database. The significant factors were screened out, and then those factors were utilized to build two valuable nomograms. The discriminative ability of nomograms was investigated using concordance-index (C-index), while the predictive accuracy and benefits were evaluated using calibration curves and decision curve analysis. Finally, a total of 417 breast Paget disease patients were enrolled. Tumor grade, histological type, American Joint Committee on Cancer (AJCC) stage, surgery, chemotherapy, and marital status were confirmed as independent overall survival (OS)-related factors; tumor grade, histological type, AJCC stage, and age were associated with independent cancer-specific survival (CSS)-related factors. The values of the C-index for OS nomogram acquired were 0.827 and 0.745 for training and validation cohorts, respectively. Meanwhile, the corresponding values of the C-index to CSS nomogram were 0.890 and 0.655, respectively. The calibration curves and decision curve analysis indicated that both nomograms had an excellent performance. Finally, the nomogram-based risk stratification system indicated that all breast Paget disease patients could be classified into low- and high-risk groups and showed distinct outcomes. In conclusion, two valuable nomograms incorporating various clinicopathological indicators were established for breast Paget disease patients. These prognostic nomograms provide accurate prognostic assessment for breast Paget disease patients and help clinicians select appropriate treatment strategies.

Nomogram to Predict Tumor-Infiltrating Lymphocytes in Breast Cancer Patients

Background: Tumor-infiltrating lymphocytes (TILs) play important roles in the prediction of prognosis and neoadjuvant therapy (NAT) efficacy in breast cancer (BRCA) patients, in this study, we identified clinicopathological factors related to BRCA TILs, then to construct and validate nomogram to predict high density of TILs.Methods: A total of 826 patients diagnosed with BRCA in Sun Yat-Sen University cancer center were enrolled in nomogram cohort. TILs were assessed using hematoxylin-eosin (H&amp;E) staining by two pathologists. Complete clinical data were collected for analysis. Then the enrolled patients were split into a training set and validation set at a ratio of 8:2. and the backward multivariate binary logistic regression model was used to establish nomogram for predicting BRCA TILs, which were further evaluated and validated using the C-index, receiver operating characteristic (ROC) curves and calibration curves. Then another independent NAT cohort of 106 patients was established for verifying this nomogram in NAT efficacy prediction.Results: TILs were significantly correlated with body mass index (BMI), tumor differentiation, ER, PR, HER2 expression, Ki67, blood biochemical indicators including total bilirubin (TBIL), indirect bilirubin (IBIL), total protein (TP), Globulin (GLOB), inorganic phosphorus (IP), calcium (Ca). In which ER expression level [OR = 0.987, 95%CI (0.982–0.992), p &lt; 0.001], IP [OR = 4.462, 95%CI (1.171∼17.289), p = 0.029], IBIL [OR = 0.906, 95%CI (0.845–0.966), p = 0.004] and TP [OR = 1.053, 95%CI (1.010–1.098, p = 0.016)] were independent predictors of TILs. Then nomogram was established, for which calibration curves (C-index = 0.759) and ROC curve (AUC = 0.759, 95%CI 0.717–0.801) in training sets, calibration curves (C-index = 0.708) and ROC curve (AUC = 0.708, 95%CI 0.617–0.800) in validation sets demonstrated great evaluation efficiency. Besides, independent NAT cohort verified this nomogram can distinguish patients with greater NAT efficacy (p = 0.041).Conclusion: The finds of clinicopathological factors associated with TILs could help clinicians to understand the tumor immunity of BRCA and improve treatment system for patients, and the established nomogram with high evaluation efficiency may be used as a complement tool for distinguishing patients with better NAT efficacy.