Acdlab processor academic edition

¹H-NMR spectra were recorded at 300 K using a Varian UNITY INOVA 500 spectrometer operating at 499.839 MHz for proton and equipped with a 5 mm double resonance probe (Agilent Technologies, CA, USA). The acquisition parameters of the ¹H-NMR spectra are reported in our previous article (85 (link)). NMR spectra were processed using an ACDlab Processor Academic Edition (Advanced Chemistry Development, 12.01, 2010). After Fourier transformation with 0.3 Hz line broadening, ¹H-NMR spectra were phased and baseline corrected and chemical shifts referenced to the signal of internal standard TSP at δ= 0.0 ppm. The spectral region comprising the signal of residual water and urea (4.7–4.9 ppm) was removed. The ACD Labs intelligent bucketing method was used for spectral integration (86 (link)). A 0.04 ppm bucket has been applied. The area of bucket regions were normalized to the total spectral area to compensate the different dilutions of original urine samples. Finally, the spectral data was imported into the SIMCA software (Version 15.0, Sartorius Stedim Biotech, Umea, Sweden) for statistical multivariate analysis. All imported data were then pre-processed using Pareto scaling (87 (link)).

NMR spectra were phased, and baseline corrected using an ACDlab Processor Academic Edition (Advanced Chemistry Development, 12.01, 2010) and chemical shifts referenced internally to TSP at d = 0.0 ppm. Next, the spectral range containing the residual water signal (4.7–4.9 ppm) was excluded. The final analyzed spectral regions were defined between 0.7–4.7 ppm and 4.9–9.5 ppm. Spectral integration was carried out using the ACD Labs intelligent bucketing method [58 (link)]. A bucket width of 0.04 ppm with a 50% looseness factor was used. This flexibility allows the bucket width to deviate slightly from the set value. The intelligent bucketing technique identifies local minima within the spectra and adjusts the bucket positions accordingly. This approach ensures that peaks are integrated into their respective buckets, even when minor chemical shift differences are present due to factors like pH variations. The areas of the bucketed regions were normalized using Median Fold Change Normalization (MFC) [59 (link)], a method particularly favored when working with urine samples compared to total sum normalization.

NMR spectra were phased and baseline-corrected using ACD/Lab Processor Academic Edition (Advanced Chemistry Development, 12.01, 2010) and chemical shifts referenced internally to TSP at d = 0.0 ppm. Next, the spectral region comprising the signal of residual water (4.7–4.9 ppm) was removed. The final spectral regions considered were in the ranges of 0.7–4.7 ppm and 4.9–9.5 ppm. The ACD Labs intelligent bucketing method was used for spectral integration (20). A 0.04 ppm bucket width was defined with an allowed 50% looseness. The degree of looseness allows the bucket width to vary over a particular value from the set bucket value. The intelligent bucket method identifies local minima in the spectra and sets the buckets accordingly. In this manner, a peak is integrated into one bucket, although there may be minor chemical shift differences due to pH, for instance.
The area of bucketed regions was normalized using median fold change normalization (MFC) [37 (link)], primarily preferred to total sum normalization when studying urine samples. Finally, the spectral data were imported into the SIMCA software (Version 16.0, Sartorius Stedim Biotech, Umea, Sweden) for multivariate statistical analysis. All imported data were then preprocessed using Pareto scaling [38 (link)].