Enhancing Solid-Phase Extraction of Tamoxifen and Its Metabolites from Human Plasma Using MOF-Integrated Polyacrylonitrile Composites: A Study on CuBTC and ZIF-8 Efficacy.

This study investigates electrospun fibers of metal-organic frameworks (MOFs), particularly CuBTC and ZIF-8, in polyacrylonitrile (PAN) for the solid-phase extraction (SPE) of Tamoxifen (TAM) and its metabolites (NDTAM, ENDO, and 4OHT) from human blood plasma. The focus is on the isolation, pre-concentration, and extraction of the analytes, aiming to provide a more accessible and affordable breast cancer patient-monitoring technology. The unique physicochemical properties of MOFs, such as high porosity and surface area, combined with PAN's stability and low density, are leveraged to improve SPE efficiency. The study meticulously examines the interactions of these MOFs with the analytes under various conditions, including elution solvents and protein precipitators. Results reveal that ZIF-8/PAN composites outperform CuBTC/PAN and PAN alone, especially when methanol is used as the protein precipitator. This superior performance is attributed to the physicochemical compatibility between the analytes' properties, like solubility and polarity, and the MOFs' structural features, including pore flexibility, active site availability, surface polarity, and surface area. The findings underscore MOFs' potential in SPE applications and provide valuable insights into the selectivity and sensitivity of different MOFs towards specific analytes, advancing more efficient targeted extraction methods in biomedical analysis.

Discriminant analysis and machine learning approach for evaluating and improving the performance of immunohistochemical algorithms for COO classification of DLBCL.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is classified into germinal center-like (GCB) and non-germinal center-like (non-GCB) cell-of-origin groups, entities driven by different oncogenic pathways with different clinical outcomes. DLBCL classification by immunohistochemistry (IHC)-based decision tree algorithms is a simpler reported technique than gene expression profiling (GEP). There is a significant discrepancy between IHC-decision tree algorithms when they are compared to GEP. METHODS: To address these inconsistencies, we applied the machine learning approach considering the same combinations of antibodies as in IHC-decision tree algorithms. Immunohistochemistry data from a public DLBCL database was used to perform comparisons among IHC-decision tree algorithms, and the machine learning structures based on Bayesian, Bayesian simple, Naïve Bayesian, artificial neural networks, and support vector machine to show the best diagnostic model. We implemented the linear discriminant analysis over the complete database, detecting a higher influence of BCL6 antibody for GCB classification and MUM1 for non-GCB classification. RESULTS: The classifier with the highest metrics was the four antibody-based Perfecto-Villela (PV) algorithm with 0.94 accuracy, 0.93 specificity, and 0.95 sensitivity, with a perfect agreement with GEP (κ = 0.88, P < 0.001). After training, a sample of 49 Mexican-mestizo DLBCL patient data was classified by COO for the first time in a testing trial. CONCLUSIONS: Harnessing all the available immunohistochemical data without reliance on the order of examination or cut-off value, we conclude that our PV machine learning algorithm outperforms Hans and other IHC-decision tree algorithms currently in use and represents an affordable and time-saving alternative for DLBCL cell-of-origin identification.

[Participation of nitric oxide and arachidonic acid metabolites via cytochrome - P450 in the regulation of arterial blood pressure]. / Participación del óxido nítrico y los metabolitos del ácido araquidónico vía citocromo P450 en la regulación de la presión arterial.

Nitric oxide and cytochrome P450 arachidonic acid metabolites participate in blood pressure regulation. The synthesis of these autacoids leads to arterial hypertension. However, it is not known whether there is an interaction between them. Therefore, we studied the modulatory effect of nitric oxide and cytochrome P450-arachidonic acid metabolites, their interaction on blood pressure, and the renal content of cytochrome P450. Male Wistar rats were divided: 1) control, 2) L-NAME (100 mg/kg/d p.o.), 3) L-NAME + SnCl2 (10 mg/kg/d i.p.), and 4) L-NAME + dexamethasone (1 mg/kg/d s.c.). We measured blood pressure and collected urine and blood for nitric oxide measurement. NO2 was quantified by HPLC. Blood pressure was: control, 97 +/- 7 mmHg; L-NAME, 151 +/- 4.6 mmHg; L-NAME + SnCl2, 133 +/- 3 mmHg, and L-NAME + dexamethasone 152 +/- 4.5 mmHg. Urine nitrite concentration was: 1) 1.832 +/- 0.32, 2) 1.031 +/- 0.23, 3) 1.616 +/- 0.33, and 4) 1.244 +/- 0.33 mumol/mL, while the concentration in blood was: 1) 0.293 +/- 0.06, 2) 0.150 +/- 0.05, 3) 0.373 +/- 0.13, and 4) 0.373 +/- 0.07 mumol/mL. L-NAME + SnCl2 decreased cytochrome P450 renal content, and L-NAME + dexamethasone showed a similar response. In conclusion, both, nitric oxide and CYP-arachidonic acid metabolites play a role in the regulation of blood pressure. Nitric oxide also partially regulates renal cytochrome P450 content.

Participación del óxido nítrico y los metabolitos del ácido araquidónico vía citocromo P450 en la regulación de la presión arterial / Participation of nitric oxide and arachidonic acid metabolites via cytochrome-p450 in the regulation of arterial blood pressure

El óxido nítrico y los metabolitos del ácido araquidónico vía citocromo P450 contribuyen a la regulación de la presión arterial. La modificación en la síntesis de estos autacoides conduce a hipertensión arterial, sin embargo, se desconoce si existe interacción. Por ello, decidimos estudiar el papel modulador del óxido nítrico y los metabolitos del ácido araquidónico vía citocromo P450, y su interacción, sobre la presión arterial y el contenido renal de citocromo P450. Ratas Wistar macho fueron divididas por grupos: 1) Control, 2) L-NAME (100mg/kg/d v.o.), 3) L-NAME + SnCl2 (10mg/kg/d i.p.) y 4) L-NAME + dexametasona (1mg/kg/d s.c.). Se determinó la presión arterial sistólica y la concentración de nitritos por HPLC en orina y sangre. Los valores de presión arterial sistólica fueron: control 97 ± 7 mmHg, L-NAME 151 ± 4.6 mmHg, L-NAME + SnCl2 133 ± 3 mmHg, y L-NAME + dexametasona 152 ± 4.5 mmHg. Los nitritos en orina fueron: 1) 1.832 ± 0.32, 2) 1.031 ± 0.23, 3) 1.616 ± 0.33 y 4) 1.244 ± 0.33 μmol/mL y en sangre: 1) 0.293 ± 0.06, 2) 0.150 ± 0.05, 3) 0.373 ± 0.13 y 4) 0.373 ± 0.07 μmol/mL. El contenido renal de citocromo P450 fue abatido con el tratamiento de L-NAME + SnCl2, y una respuesta semejante se observó con L-NAME + dexametasona. Tanto óxido nítrico como los metabolitos del ácido araquidónico vía CYP participan en la regulación de la presión arterial. Además, el óxido nítrico contribuye regulando parcialmente el contenido renal del citocromo P450.

Nitric oxide and cytochrome P450 arachidonic acid metabolites participate in blood pressure regulation. The synthesis of these autacoids leads to arterial hypertension. However, it is not known whether there is an interaction between them. Therefore, we studied the modulatory effect of nitric oxide and cytochrome P450-arachidonic acid metabolites, their interaction on blood pressure, and the renal content of cytochrome P450. Male Wistar rats were divided: 1) control, 2) L-NAME (100 mg/kg/d p.o.), 3) L-NAME + SnCl2 (10 mg/kg/d i.p.), and 4) L-NAME + dexamethasone (1 mg/kg/d s.c.). We measured blood pressure and collected urine and blood for nitric oxide measurement. NO2 was quantified by HPLC. Blood pressure was: control, 97 ± 7 mmHg; L-NAME, 151 ± 4.6 mmHg; L-NAME + SnCl2, 133 ± 3 mmHg, and L-NAME + dexamethasone 152 ± 4.5 mmHg. Urine nitrite concentration was: 1) 1.832 ± 0.32, 2) 1.031 ± 0.23, 3) 1.616 ± 0.33, and 4) 1.244 ± 0.33 μmol/mL, while the concentration in blood was: 1) 0.293 ± 0.06, 2) 0.150 ± 0.05, 3) 0.373 ± 0.13, and 4) 0.373 ± 0.07 μmol/ mL. L-NAME + SnCl2 decreased cytochrome P450 renal content, and L-NAME + dexamethasone showed a similar response. In conclusion, both, nitric oxide and CYP-arachidonic acid metabolites play a role in the regulation of blood pressure. Nitric oxide also partially regulates renal cytochrome P450 content. (Arch Cardiol Mex 2003; 73:98-104).