As a new type of porous crystalline composite material, MOF-COF has shown great advantages in metal separation. Herein, a CoMOF-COF was designed for highly selective separation of trace Pb2+ ions. The designed CoMOF-COF has a high density of nitrogen-oxygen functional groups and can selectively separate metal ions. There is a strong affinity between the designed CoMOF-COF material and metal Pb2+ ions, which can be attributed to the ordered heterogeneous porous structure and large amounts of nitrogen-and oxygen-containing functional groups. The composite showed high adsorption selectivity for Pb2+ ions and had adsorption capacity of 33 mg g-1, with high chemical stability. Based on this solid phase extraction material, a high sensitivity detection method for Pb2+ ions was established, which has the detection limit of 37.3 ng L-1, precision of 1.9 %. Linear detection range is 0.2-10 ng mL-1, and the detection of Pb2+ ions in actual water samples was realized. Through this study, it is proved that the strong affinity between the designed CoMOF-COF materials and metal Pb2+ ions can be attributed to the soft and hard acid-base theory, which reveals the structure-activity relationship between the porous heterostructure of such materials and metal separation, providing a highly selective separation material for the separation of other environmental pollutants.

This study is focused on fractionation of insulin-like growth factor I (IGF-I) and transforming growth factor-β2 (TGF-β2) using a new electro-based membrane process calledelectrodialysis with filtration membranes (EDFM). Before EDFM, different pretreatments were tested, and four pH conditions (4.25, 3.85, 3.45, and 3.05) were used during EDFM. It was demonstrated that a 1:1 dilution of defatted colostrum with deionized water to decrease mineral content followed by the preconcentration of GFs by UF is necessary and allow for these compounds to migrate to the recovery compartment during EDFM. MS analyses confirmed the migration, in low quantity, of only α-lactalbumin (α-la) and β-lactoglobulin (β-lg) from serocolostrum to the recovery compartment during EDFM. Consequently, the ratio of GFs to total protein in recovery compartment compared to that of feed serocolostrum solution was 60× higher at pH value 3.05, the optimal pH favoring the migration of IGF-I and TGF-β2. Finally, these optimal conditions were tested on acid whey to also demonstrate the feasibility of the proposed process on one of the main by-products of the cheese industry; the ratio of GFs to total protein was 2.7× higher in recovery compartment than in feed acid whey solution, and only α-la migrated. The technology of GF enrichment for different dairy solutions by combining ultrafiltration and electrodialysis technologies was proposed for the first time.

UNASSIGNED: To analyze marital outcomes, divorce or separation, and its association with demographic, socioeconomic, and clinicopathological factors among breast cancer (BC) survivors after 2-years of diagnosis.
UNASSIGNED: We performed a retrospective analysis of marital status at baseline and at years 1 and 2 of follow-up of women aged ≥ 18 years diagnosed with invasive BC participating in the AMAZONA III (GBECAM0115) study. The BC diagnosis occurred between January 2016 and March 2018 at 23 institutions in Brazil.
UNASSIGNED: Of the 2974 women enrolled in AMAZONA III, 599 were married or living under common law at baseline. Divorce or separation occurred in 35 (5.8%) patients at 2 years of follow-up. In the multivariate analysis, public health insurance coverage was associated with a higher risk of marital status change (8.25% vs. 2.79%, RR 3.09, 95% CI 1.39 - 7.03, p = 0.007). Women who underwent mastectomy, adenomastectomy or skin-sparing mastectomy were associated with a higher risk of divorce or separation (8.1% vs. 4.49%, RR 1.97, 95 CI 1.04 - 3.72, p = 0.0366) than those who underwent breast-conserving surgery.
UNASSIGNED: Women covered by the public health system and those who underwent mastectomy, adenomastectomy or skin-sparing mastectomy were associated with a higher risk of divorce or separation. This evidence further supports the idea that long-term marital stability is associated with a complex interplay between socioeconomic conditions and stressors, such as BC diagnosis and treatment. ClinicalTrials Registration: NCT02663973.

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Microplastics is known to be ubiquitous in aquatic environment. Quantification of microplastics in natural waters is an important problem of analytical chemistry, the solution of which is needed for the assessment of water quality and potential risks for water inhabitants and consumers. Separation methods play a key role in the correct quantification of microplastics in natural waters. In the present study the applicability of countercurrent chromatography to the continuous-flow separation and preconcentration of microplastics from water samples in rotating coiled column (RCC) using water-oil systems has been demonstrated for the first time. The effect of column rotation speed and mobile phase (water) flow rate on the retention of the stationary (oil) phase in RCC is studied. The retention parameters of 10 vegetable and 2 synthetic oils are determined. Castor, olive, rapeseed, soybean, linseed, sesame, and sunflower oils are found to be applicable to the separation of microplastics from water samples using RCC. Taking as example polyethylene microparticles of different size (40-63, 63-100, and 100-250 μm), the high recovery of microplastics (about 100 %) from aqueous phase into castor and rapeseed oils is shown. The method has been proven to be efficient for the separation of microplastics from simulated fresh and sea natural waters. It may be perspective not only for the quantification of microplastics in natural waters but as well as for the purification of wastewaters containing microplastics.

A macrocyclic peptide A was successfully purified in large quantities (∼30 g) in >95 % purity by an integrated two-step orthogonal purification process combining supercritical fluid chromatography (SFC) with medium-pressure reverse-phase liquid chromatography (MP-RPLC). MP-RPLC was used to fractionate the crude peptide A, remove unwanted trifluoroacetic acid (TFA) originating from the peptide A cleavage off the resin, and convert the peptide A into ammonium acetate salt form, prior to the final purification by SFC. A co-solvent of methanol/acetonitrile containing ammonium acetate and water in CO2 was developed on a Waters BEH 2-Ethylpyridine column. The developed SFC method was readily scaled up onto a 5 cm diameter column to process multi-gram quantities of the MP-RPLC fraction to reach > 95 % purity with a throughput/productivity of 0.96 g/h. The incorporation of SFC with MP-RPLC has been demonstrated to have a broader application in other large-scale polypeptide purifications.

BACKGROUND: In binary classification for clinical studies, an imbalanced distribution of cases to classes and an extreme association level between the binary dependent variable and a subset of independent variables can create significant classification problems. These crucial issues, namely class imbalance and complete separation, lead to classification inaccuracy and biased results in clinical studies.
METHODS: To deal with class imbalance and complete separation problems, we propose using a fuzzy logistic regression framework for binary classification. Fuzzy logistic regression incorporates combinations of triangular fuzzy numbers for the coefficients, inputs, and outputs and produces crisp classification results. The fuzzy logistic regression framework shows strong classification performance due to fuzzy logic\'s better handling of imbalance and separation issues. Hence, classification accuracy is improved, mitigating the risk of misclassified conditions and biased insights for clinical study patients.
RESULTS: The performance of the fuzzy logistic regression model is assessed on twelve binary classification problems with clinical datasets. The model has consistently high sensitivity, specificity, F1, precision, and Mathew\'s correlation coefficient scores across all clinical datasets. There is no evidence of impact from the imbalance or separation that exists in the datasets. Furthermore, we compare the fuzzy logistic regression classification performance against two versions of classical logistic regression and six different benchmark sources in the literature. These six sources provide a total of ten different proposed methodologies, and the comparison occurs by calculating the same set of classification performance scores for each method. Either imbalance or separation impacts seven out of ten methodologies. The remaining three produce better classification performance in their respective clinical studies. However, these are all outperformed by the fuzzy logistic regression framework.
CONCLUSIONS: Fuzzy logistic regression showcases strong performance against imbalance and separation, providing accurate predictions and, hence, informative insights for classifying patients in clinical studies.

To improve the selective separation performance of silica nanofibers (SiO2 NFs) for cesium ions (Cs+) and overcome the defects of Prussian blue nanoparticles (PB NPs), PB/SiO2-NH2 NFs were prepared to remove Cs+ from water. Among them, 3-aminopropyltriethoxysilane (APTES) underwent an alkylation reaction with SiO2, resulting in the formation of a dense Si-O-Si network structure that decorated the surface of SiO2 NFs. Meanwhile, the amino functional groups in APTES combined with Fe3+ and then reacted with Fe2+ to form PB NPs, which anchored firmly on the aminoated SiO2 NFs surface. In our experiment, the maximum adsorption capacity of PB/SiO2-NH2 NFs was 111.38 mg/g, which was 31.5 mg/g higher than that of SiO2 NFs. At the same time, after the fifth cycle, the removal rate of Cs+ by PB/SiO2-NH2 NFs adsorbent was 75.36% ± 3.69%. In addition, the adsorption isotherms and adsorption kinetics of PB/SiO2-NH2 NFs were combined with the Freundlich model and the quasi-two-stage fitting model, respectively. Further mechanism analysis showed that the bond between PB/SiO2-NH2 NFs and Cs+ was mainly a synergistic action of ion exchange, electrostatic adsorption and membrane separation.

Semiparametric probabilistic index models allow for the comparison of two groups of observations, whilst adjusting for covariates, thereby fitting nicely within the framework of generalized pairwise comparisons (GPC). As with most regression approaches in this setting, the limited amount of data results in invalid inference as the asymptotic normality assumption is not met. In addition, separation issues might arise when considering small samples. In this article, we show that the parameters of the probabilistic index model can be estimated using generalized estimating equations, for which adjustments exist that lead to estimators of the sandwich variance-covariance matrix with improved finite sample properties and that can deal with bias due to separation. In this way, appropriate inference can be performed as is shown through extensive simulation studies. The known relationships between the probabilistic index and other GPC statistics allow to also provide valid inference for example, the net treatment benefit or the success odds.

Recent advancements in the applications of heavy minerals by modern science, engineering, technological and metallurgical industries especially in the demand by nuclear and power industries have significantly increased over the decades. This is the reason for the criticality and commerciality of products of heavy minerals and also necessitated their high demand by industries. The recovery of heavy minerals, such as: Zr and Ti associated minerals from their deposits is dependent on extractive metallurgy of transition and refractory metals from complex minerals. Based on the effectiveness and efficiency of mineral concentration as well as metal extraction, several challenges have been encountered in their recovery process, especially in their separation from associated mineral impurities or gangue. This review is however focused on investigating magnetic and electrostatic physical processing techniques and their applications in the beneficiation and recovery of heavy minerals. This will therefore, serve as a tool in reducing process steps and extraction complexity involved in downstream measures of dissolution and hydrometallurgical processes of the minerals.