Significant Correlation between Salivary and Serum Ca 15-3 in Healthy Women and Breast Cancer Patients

Laidi, Fatna,Bouziane, Amal,Lakhdar, Amina,Khabouze, Samira,Amrani, Mariam,Rhrab, Brahim,Zaoui, Fatima Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.11

The tumor marker CA 15-3 is one of the most import reliable for metastatic breast cancer monitoring. While it is generally assessed in serum of patients, blood sampling is an invasive method compared to saliva sampling which is simple and could be an alternative to blood according to many studies. The aim of this investigation was to assess the relationship between serum and salivary concentrations of the protein CA 15-3 in patients with breast cancer and healthy asymptomatic volunteers. A case-control study was conducted with 60 women: 29 breast cancer patients from the Maternity Hospital Souissi Rabat (Morocco) and 31 healthy asymptomatic women. The CA 15-3 concentrations in saliva and serum samples were assessed using an enzyme immune assay (EIA kits) and comparison between cases and controls was made by the Mann-Whitney test. The correlation between serum and saliva CA 15-3 concentration was tested using Pearson correlation. The comparison result of CA15-3 concentration in saliva and serum level in cases and controls was not statistically significant (p>0.05). However, the correlation between salivary and serum CA 15-3 concentration was positive and statistically significant (r=0.27, p=0.03). In conclusion, the positive correlation between salivary and serum expression found in our study suggests that saliva could be an alternative to blood sampling to help breast cancer monitoring.

Usefulness of Salivary and Serum Auto-antibodies Against Tumor Biomarkers HER2 and MUC1 in Breast Cancer Screening

Laidi, Fatna,Bouziane, Amal,Errachid, Abdelhamid,Zaoui, Fatima Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.1

Background: The aim of this work was to investigate if serum and salivary auto-antibodies, isotypes IgG and IgM, against HER2 and MUC1 tandem repeat fragments could play a role in breast cancer screening. Materials and Methods: Our case-control study was conducted in breast cancer patients, in early stages (n=29), at the gynecology service, Maternity Souissi Hospital, Rabat, Morocco and healthy woman (n=31). Salivary and serum auto-antibodies against HER2 and MUC1 (tandem repeat) were assessed by enzyme-linked immunosorbent assay (ELISA) and compared between patients and healthy women using the Mann-Whitney U test. A P-value <0.05 was considered to be statistically significant. Results: Our data showed higher expression of all serum and salivary autoantibodies in patients as compared to healthy women p<0.05. However, serum IgM anti-MUC1 expression did not show a significant difference between cases and controls (p=0.79). Similarly, salivary IgG anti-HER2 expression did not differ (p=0.15). The correlation between the different isotypes of antibodies revealed that the highest correlation was between salivary IgG anti-HER2 and salivary IgG anti-MUC1(r=0.65). In fact, we have found in saliva the correlation between autoantibodies anti-MUC1 and anti-HER2 more important than in serum (r=0.59 and r=0. 55). However, the correlation between serum and saliva values for all antibodies was weak. Conclusions: Autoantibodies against HER2 and MUC1 may provide a useful approach in breast cancer screening when using both serum and saliva values.

MicroRNA analysis reveals the role of miR-214 in duck adipocyte differentiation

Wang Laidi,Hu Xiaodan,Wang Shasha,Yuan Chunyou,Wang Zhixiu,Chang Guobin,Chen Guohong 아세아·태평양축산학회 2022 Animal Bioscience Vol.35 No.9

Objective: Fat deposition in poultry is an important factor in production performance and meat quality research. miRNAs also play important roles in regulating adipocyte differentiation process. This study was to investigate the expression patterns of miRNAs in duck adipocytes after differentiation and explore the role of miR-214 in regulating carnitine palmitoyltransferases 2 (CPT2) gene expression during duck adipocyte differentiation. Methods: Successful systems for the isolation, culture, and induction of duck primary fat cells was developed in the experiment. Using Illumina next-generation sequencing, the miRNAs libraries of duck adipocytes were established. miRanda was used to predict differentially expressed (DE) miRNAs and their target genes. The expression patterns of miR-214 and CPT2 during the differentiation were verified by quantitative real-time polymerase chain reaction and western blot. Luciferase reporter assays were used to explore the specific regions of CPT2 targeted by miR-214. We used a miR-214 over-expression strategy in vitro to further investigate its effect on differentiation process and CPT2 gene transcription. Results: There were 481 miRNAs identified in duck adipocytes, included 57 DE miRNA candidates. And the 1,046 targets genes of DE miRNAs were mainly involved in p53 signaling, FoxO signaling, and fatty acid metabolism pathways. miR-214 and CPT2 showed contrasting expression patterns before and after differentiation, and they were selected for further research. The expression of miR-214 was decreased during the first 3 days of duck adipocytes differentiation, and then increased, while the expression of CPT2 increased both in the transcriptional and protein level. The luciferase assay suggested that miR-214 targets the 3’untranslated region of CPT2. Overexpression of miR-214 not only promoted the formation of lipid droplets but also decreased the protein abundance of CPT2. Conclusion: Current study reports the expression profile of miRNAs in duck adipocytes differentiated for 4 days. And miR-214 has been proved to have the regulator potential for fat deposition in duck. Objective: Fat deposition in poultry is an important factor in production performance and meat quality research. miRNAs also play important roles in regulating adipocyte differentiation process. This study was to investigate the expression patterns of miRNAs in duck adipocytes after differentiation and explore the role of miR-214 in regulating carnitine palmitoyltransferases 2 (CPT2) gene expression during duck adipocyte differentiation.Methods: Successful systems for the isolation, culture, and induction of duck primary fat cells was developed in the experiment. Using Illumina next-generation sequencing, the miRNAs libraries of duck adipocytes were established. miRanda was used to predict differentially expressed (DE) miRNAs and their target genes. The expression patterns of miR-214 and CPT2 during the differentiation were verified by quantitative real-time polymerase chain reaction and western blot. Luciferase reporter assays were used to explore the specific regions of CPT2 targeted by miR-214. We used a miR-214 over-expression strategy in vitro to further investigate its effect on differentiation process and CPT2 gene transcription.Results: There were 481 miRNAs identified in duck adipocytes, included 57 DE miRNA candidates. And the 1,046 targets genes of DE miRNAs were mainly involved in p53 signaling, FoxO signaling, and fatty acid metabolism pathways. miR-214 and CPT2 showed contrasting expression patterns before and after differentiation, and they were selected for further research. The expression of miR-214 was decreased during the first 3 days of duck adipocytes differentiation, and then increased, while the expression of CPT2 increased both in the transcriptional and protein level. The luciferase assay suggested that miR-214 targets the 3’untranslated region of CPT2. Overexpression of miR-214 not only promoted the formation of lipid droplets but also decreased the protein abundance of CPT2.Conclusion: Current study reports the expression profile of miRNAs in duck adipocytes differentiated for 4 days. And miR-214 has been proved to have the regulator potential for fat deposition in duck.

Modeling and optimization of small-scale NF/RO seawater desalination using the artificial neural network (ANN)

Asma Adda,Salah Hanini,Salah Bezari,Maamar Laidi,Mohamed Abbas 대한환경공학회 2022 Environmental Engineering Research Vol.27 No.2

The performance of seawater hybrid NF/RO desalination plant including permeate conductivity; permeate flow rate and permeate recovery. Under different feed parameters time, inlet temperature, inlet pressure, inlet conductivity and inlet flow rate were modelled by Artificial Neural Network (ANN) back-propagation based on Levenberg– Marquardt training algorithm. The optimal ANN model had a 5-8-3 architecture with a hyperbolic tangent transfer function in hidden layer and linear transfer function at the output layer. The ability of ANN performed model was compared with multiple linear regression (MLR). The results show that MLR is not satisfactory for predicting the performance of NF/RO hybrid desalination process with a correlation coefficient about 0.6. The trained ANN model has presented a good agreement between the prediction and the experimental data during the training with reasonable statistical metrics values (RMSE, MAE and AARD). The coefficient of determination values for the prediction of permeate conductivity, permeate flow rate and recovery by ANN were 0.969, 0.942, and 0.963, respectively. Therefore, the ANN model can successfully predict the performance of NF/RO hybrid seawater desalination plant.

Modeling of a Dynamic Membrane Filtration Process Using ANN and SVM to Predict the Permeate Flux

Soufyane Ladeg,Mohamed Moussaoui,Maamar Laidi,Nadji Moulai-Mostefa 한국막학회 2023 멤브레인 Vol.33 No.1

Two computational intelligence techniques namely artificial neural networks (ANN) and support vector machine (SVM) are employed to model the permeate flux based on seven input variables including time, transmembrane pressure, rotating velocity, the pore diameter of the membrane, dynamic viscosity, concentration and density of the feed fluid. The best-fit model was selected through the trial-error method and the two statistical parameters including the coefficient of determination (R2 ) and the average absolute relative deviation (AARD) between the experimental and predicted data. The obtained results reveal that the optimized ANN model can predict the permeate flux with R2 = 0.999 and AARD% = 2.245 versus the SVM model with R2 = 0.996 and AARD% = 4.09. Thus, the ANN model is found to predict the permeate flux with high accuracy in comparison to the SVM approach.