Macrofuran quantitative determination using the colorimetric method

From our previous study of the UV-absorption spectrum of the nanο-La complex presented in [4], it showed six absorption peaks at “266, 315, 397, 473, 588 and 642 nm due to the intra-ligand π- π*, n-π*, and LMCT” [4]. However, the 25 ng/mL macrofuran@nano-La complex exhibited six UV–vis peaks at 254, 313, 381, 479, 545, and 628 nm as represented in Fig. 1a. Comparing the absorption spectra of nano-La complex with the macrofuran@nano-La-complex, we noted a blueshift for the all peaks except at the peak at 480 nm, a red-shift is observed (from 266 to 254 nm; 315 to 313 nm; 397 to 381 nm; 588 to 545 nm; 642 to 628 nm “blueshift”; and from 473 to 479 nm “red-shift”). In addition to, significantly increasing the intensities of the peaks at 316, 381 and 479 nm (sharp peaks).

Fig. 1

a The UV-absorption spectrum of the nano-La complex (red color) and in with addition of 25 ng/mL macrofuran (black color). b The UV-absorption spectrum of the nano-La complex against different concentrations of macrofuran at 479 nm. c A smartphone photography image for color change of the nano-La complex with increasing the concentrations of macrofuran

The nano-La complex was tested as a colοrimetric chemosensor for the macrofuran detection and quantification. The UV-absorption spectrum of the nanο-La-complex was investigated against different concentrations of macrofuran, and the results were presented in Fig. S1. As revealed in Fig. S1, we can be observed a significant increase of the absorption spectra peaks at 313, 381, and 479 nm.

Focusing on the sharp peak at 479 nm showed a red-shift with about 6 nm with a color change from orange-yellow to red color (Fig. 1b). Additionally, by increasing the macrofuran concentration from 1.0 to 100.0 ng/mL the absorption peak intensities increased gradually. Moreover, the colors of the nano-La complex solutions were converted from orange-yellow to red color shown in Fig. 1c. Accordingly, the nano-La complex could be used as a naked eye indicator for macrofuran and colorimetric chemosensor.

Under the optimum conditions, as presented in Fig. 2a, a linear relationship was achieved between the nano-La complex absorbance intensities and different macrofuran concentrations. On the absorption peak intensities at 479 nm (Ab479), the calibration curves of the proposed colοrimetric method showed stability response in a wide concentration in a range of 1.0–100.0 ng/mL, and the fitted Eqs. (1) can express as:

Fig. 2

a A linear relationship (calibration graph) between the nano-La complex absorbance intensities and different macrofuran concentrations. b A histogram of evaluation of the absorption intensity of the nano-La complex towards the macrofuran against different types of interfering analytes. c A histogram of evaluation of inter-day accuracy and precision for the colorimetric method. d A histogram of evaluation of intra-day accuracy, and precision for the colorimetric method

$$\mathrm\left(}_\right)=1.175+0.038\;\left[\mathrm\right] \mathrm^=0.9973,$$

(1)

The colorimetric method-based on nano-La complex exhibited excellent sensitivity towards macrofuran with a detection limit (LOD) of 0.175 ng/mL and quantification limit (LOQ) of 0.53 ng/mL; the summarized of best optimized conditions for the proposed colοrimetric method and regression parameters was presented in Table 1. Comparison of the present method with previously published work [1,2,3,4, 20,21,22,23,24,25,26] was presented in Table S1.

Table 1 Sensitivity and regression parameters for colorimetric method

The effects of pH and temperature on the absorption peak intensities at 479 nm (Ab479) of the present colorimetric method at different macrofuran concentrations were investigated. The results revealed that changing the pH from about 3.5 to 10.5 did not seem to cause any significant changes in the absorbance intensities. However, the change in environmental temperature from 18 to 35 °C also did not seem to cause any significant changes in the absorbance intensities. The influence of the solvents on the absorption peak intensities at 479 nm (Ab479) of the present colorimetric method at concentrations also was investigated and studied. The results revealed the high absorption intensity of the system in ethanol and then water because these solvents stabilize the excited state of the sensor. However, with other solvents like acetonitrile, DMF, and DMSO, the absorption intensity of the sensor is slightly decreased and/or a blue shift due to the destabilization of the excited state by these solvents.

The evaluation of the potential selectivity and specificity of nano-La complex towards macrofuran based on the current colorimetric method was performed according to a similar study in our previous work [4]. However, herein, the absorption spectra of nano-La complex (1.0 mM) were examined against the interfering substances mention before like “Acetylsalicylic acid (ACS), Chloramphenicol (CHL), Furosemide (FUR), Furazolidone (FUZ), Glucose (GLU), Ibuprofen (IBP), Nitrobenzene (NB), Sucrose (SUC), Sulfafurazole (SUL), and Uric acid (UA)”) at the concentration level of 20.0 ng/mL for the macrofuran and interfering substances and presented in Fig. 2b. As shown in the presented histogram, the results of the Abs479 intensities were extremely enhanced with macrofuran, without changes in the case of the other interfering matrix. The obtained results were in excellent agreement with the obtained ones in our previous study [4], which revealed that the nano-La complex is extremely selective for macrofuran.

The reducibility and repeatability of the presented method were evaluated via study the inter- and intra-day accuracy and precision. This study was investigated at 5 levels of macrofuran concentrations (1.0, 5.0, 10.0, 20.0, and 50.0 ng/mL), and each reading was replicated 3 times. The histograms of Abs479 intensities for inter-/intra-days were presented in Fig. 2c and d, respectively. From the histogram, results prove the accuracy, precision, reducibility, and repeatability of the present work.

The applicability of the present colorimetric method for determination of macrofuran in different real samples (serum\plasma\urine) as well as in pharmaceutical formulations including the recoveries study was investigated. The investigation was carried out via spiking method at three concentration levels of macrofuran (1.0, 10.0, and 50.0 ng/mL) at different serum\plasma\urine samples and then evaluated the recoveries percent, and the summarized results were presented in Table S2. However, the pharmaceutical formulations of macrofuran “Capsules 100 mg” were examined at the same above levels (1.0, 10.0, and 50.0 ng/mL) of concentration and the data was presented in Table S2. From the table data, the average recoveries percent were about 97.44, 97.88, 100.67, and 98.30% for serum, plasma, urine, and pharmaceutical formulation samples, respectively. These results prove that the proposed method is applicable, sensitive, and effective, for quantification of macrofuran different pharmaceutical formulation and real samples; and this method will be a future promising analytical tool for simple and fast macrofuran detection and quantification.

Macrofuran qualitative detection using prototype-based coated paper strip

As clarified in the experimental section, the prototype-based coated paper strip was prepared by soaking the Whatman sterile membrane in a beaker containing 100 mM of nano-lanthanum complex solution overnight as shown in Fig. 3a. After that, the coated paper strips were dried at 60 °C in the oven in a petri dish as shown in Fig. 3b, and then after drying, the prototype-based coated paper strip became ready to use. By immersing this strip in 100 ng/mL of macrofuran, the color changes during 30 s from yellow to red color as shown in Fig. 3c; these strips can be used as naked eye detection of macrofuran (as macrofuran indicator). Moreover, by increasing the concentrations of macrofuran the color degree in transfer from yellow color to red degree to deep red colors as shown in Fig. 3d.

Fig. 3

A smartphone photography images for prototype-based coated paper strip preparation and optimization: a Soaking step in beaker contain nano-lanthanum complex solution. b Drying step and ready to used coated paper strips. c A coated paper strip optimization before “blank” [i] and after immersed in 100 ng/mL of macrofuran [ii]. d A change in the degree of color based on the change of concentrations of macrofuran [i, 1.0 ng/mL; ii, 5.0 ng/mL; iii, 10.0 ng/mL; iv, 20.0 ng/mL; v, 30.0 ng/mL; vi, 40.0 ng/mL; vii, 50.0 ng/mL; viii, 75.0 ng/mL; and ix, 100.0 ng/mL]

The validation and optimization of the present prototype-based coated paper strips for detection of macrofuran were investigated via study of the applicability in real samples as well as in pharmaceutical formulation, beside the interfering and selectivity evaluation, with a similar study mentioned before in the above colorimetric method. The summarized results of this investigation showed that the color of coated paper strips changed directly based on the concentration of macrofuran. Moreover, the coated paper strips showed high sensitivity toward macrofuran via color change to red, whereas nothing occurs with other interfering.

Electronic color sensor device prototype fabrication and optimization for macrofuran quantitative detection based coated paper strip

As presented in Fig. 3d, the red color intensities are directly proportional to the macrofuran concentration. So, we can benefit from the change in color of coated paper strips as a function in macrofuran concentration change via fabrication of an electronic color sensor device prototype for quantitative detection of macrofuran. The sensing fabrication strategy with programing details are discussed as follows:

TCS3200 color sensor specifications and connection process

The TCS3200 color sensor as shown in Fig. 4a generally uses a RGB sensor chip for the color detect process [27]. The details of the color sensor component and mechanism of work were presented in the supporting data file and according to Fig. 4b and c. Moreover, the details of control pin connection data are summarized in TCS3200 sensor data sheet (Table S3). Finally, the TCSP3200 sensor wiring connection to Arduino Uno according to the schematic diagram (Fig. 4d).

Fig. 4

a The TCS3200 color sensor, b TCS3200 RGB sensor chip, c the photodiode (color sensor) connected to Arduino, and d wiring the TCSP3200 sensor to your Arduino; simply follow the next schematic diagram

Preparing the sensor code for Arduino and data interpretations

Preparation the sensor code programming for Arduino and data interpretations can simplified in the following two stages:

Reading the output frequency

Reading color and displaying the concentrations according to output frequency on the monitor. The frequency values were written down when you place different colors in the color sensor. Overall, this stage carried out in the following steps:

Uploading the code to the Arduino-board according to Scheme S1.

Opening the serial-monitor at 9600 baud-rate.

To select the best distance for the sensor, in front of the sensor put a blue color object at dissimilar distances as shown in Fig. S2.

Optimizing the best distance by saving the two measurements: when the object is placed far and near from the sensor, respectively.

The values were checked on the display. The frequency of blue color (B) compared to the reading frequency of red color (R) and green color (G) should be the lower value according to Scheme S2.

At optimum blue object position at the front of the sensor, the values of the frequency of blue color (B) oscillate between 59 and 223 (see the values highlighted in Scheme S2). In our case, the frequency values (59 and 223) cannot use in code preparation. It should measure the colors for the present specific object with our own color sensor followed by saving the obtained upper and bottom frequency limits for the blue color.

Repeat the above step with red and green objects and save also the frequency limits (upper and bottom) for each color.

Characterization the different colors

The difference between colors was recorded in the program. The frequency values were calibrated according to the concentration of color previously on the program code; the sensor can distinguish between different concentrations related to RGB. Overall, the values frequency maps to RGB between 0 and 255. In the former step, the corresponding frequency at blue maximum was 59 and at higher distance was 223. So, the frequency values of 59 and 223 are corresponding to 255 and 0 in the RGB, respectively. Subsequently, according to Scheme S3 at the Arduino map, () function are replaced with your own values. Finally, to obtain the concentration through the distinguish between the change in colors by reading of the red, green, and blue values.

Now, the program compares the read value to the storge value in Table 2, and if the value is in the range of 80% of any value of the table, the program given concentration at these values. The obtained data according to macrofuran quantitative detection-based coated paper strip using the electronic color sensor device prototype is summarized in Table 2. A smartphone photo for the primary version prototype of the electronic color sensor was present in Fig. S3.

Table 2 Distinguish between different colors

Finally, all of the above results concluded that the suggested prototype device will be promising, efficient, sensitive, selective, accurate, precise, lower cost, friendly, easy test, working with different real samples (serum\plasma\urine) as well in pharmaceutical formulation for monitoring and quantification of macrofuran.