Comparison between the gas-liquid solubility of methanol and ethanol in different organic phases using structural properties of solvents

Analysis of electrocautery smoke released from the tissues frequently cut in orthopedic surgeries

BACKGROUND

Electrosurgical smoke could be different by the device of cutting or the type of tissue that is being cut.

AIM

To analyze the electrocautery smoke released from the tissues that are frequently cut in orthopedic surgeries.

METHODS

The released smoke from electrocautery of five different tissue types (meniscus, ligament, adipose, muscle, and synovium) of five patients who underwent total knee arthroplasty were collected and analyzed for volatile organic compounds (VOCs) and 27 candidate polycyclic aromatic hydrocarbons (n = 25). Surgical smoke was produced with an electrocautery device for 4 min.

RESULTS

None of the 27 evaluated polycyclic aromatic hydrocarbons compounds were detectable ‎in electrocautery smoke collected from the surgical cutting of the different tissues.‎ The number and identity of detected VOCs were similar between the patients but not between tissue types. The number of detected VOCs was the highest in synovial tissue (n = 21) and the lowest in the meniscus and adipose tissue (n = 12). ‏‎The number of toxic and/or carcinogenic VOCs were the most in the muscle and meniscus tissues (‎Toluene, Ethylbenzene, and Styrene). No ‎ toxic and/or carcinogenic VOCs were identified in the ligament and adipose tissue.

CONCLUSION

Meniscus and muscle tissue are associated with the highest number of toxic and/or carcinogenic VOCs. Therefore, we recommend that surgeons avoiding the electrocautery of these tissues.

Quantitative structure-activity relationship to predict the anti-malarial activity in a set of new imidazolopiperazines based on artificial neural networks

Background

After years of efforts on the control of malaria, it remains as a most deadly infectious disease. A major problem for the available anti-malarial drugs is the occurrence of drug resistance in Plasmodium. Developing of new compounds or modification of existing anti-malarial drugs is an effective approach to face this challenge. Quantitative structure activity relationship (QSAR) modelling plays an important role in design and modification of anti-malarial compounds by estimation of the activity of the compounds.

Methods

In this research, the QSAR study was done on anti-malarial activity of 33 imidazolopiperazine compounds based on artificial neural networks (ANN). The structural descriptors of imidazolopiperazine molecules was used as the independents variables and their activity against 3D7 and W2 strains was used as the dependent variables. During modelling process, 70% of compound was used as the training and two 15% of imidazolopiperazines were used as the validation and external test sets. In this work, stepwise multiple linear regression was applied as the valuable selection and ANN with Levenberg–Marquardt algorithm was utilized as an efficient non-linear approach to correlate between structural information of molecules and their anti-malarial activity.

Results

The sufficiency of the suggested method to estimate the anti-malarial activity of imidazolopiperazine compounds at two 3D7 and W2 strains was demonstrated using statistical parameters, such as correlation coefficient (R²), mean square error (MSE). For instance R²_train = 0.947, R²_val = 0.959, R²_test = 0.920 shows the potential of the suggested model for the prediction of 3D7 activity. Different statistical approaches such as and applicability domain (AD) and y-scrambling was also showed the validity of models.

Conclusion

QSAR can be an efficient way to virtual screening the molecules to design more efficient compounds with activity against malaria (3D7 and W2 strains). Imidazolopiperazines can be good candidates and change in the structure and functional groups can be done intelligently using QSAR approach to rich more efficient compounds with decreasing trial–error runs during synthesis.