Long-term debridement effect of denervated large sacrococcygeal pressure injury: A case report.

RATIONALE: Complicated pressure injury in paraplegic patients is common and difficult to manage. Previous case studies have documented short-term management; however, little is known regarding suitable approaches to long-term clearing of extensive pressure injury in the sacrococcygeal area under denervation. PATIENT CONCERNS: A 53-year-old man was bedridden for 1.5 years owing to cervical vertebral fracture-dislocation (C5-C6), resulting in extensive sacrococcygeal pressure injury. DIAGNOSES: On admission, he presented with the injury complicated by infection (stage IV necrosis), and his vital signs were unstable. INTERVENTIONS: The infection was treated with a range of antibiotics, including clindamycin phosphate, metronidazole, cefoperazone sodium, and sulbactam sodium. Debridement of the pressure injury was performed, helping remove the necrotic tissue and stimulate tissue regeneration. OUTCOMES: The patient was discharged after 88 days of hospitalization. The extent of the pressure injury at discharge was reduced compared with that at admission. At 4-month follow-up, the injury was nearly healed, with no signs of any further complications. LESSONS: This case study suggests that wound debridement is a cost-effective and clinically efficacious approach to long-term complicated pressure injury management.

Rapid detection and quantification of adulteration in saffron by excitation-emission matrix fluorescence combined with multi-way chemometrics.

BACKGROUND: Saffron has gained people's attention and love for its unique flavor and valuable edible value, but the problem of saffron adulteration in the market is serious. It is urgent for us to find a simple and rapid identification and quantitative estimation of adulteration in saffron. Therefore, excitation-emission matrix (EEM) fluorescence combined with multi-way chemometrics was proposed for the detection and quantification of adulteration in saffron. RESULTS: The fluorescence composition analysis of saffron and saffron adulterants (safflower, marigold and madder) were accomplished by alternating trilinear decomposition (ATLD) algorithm. ATLD and two-dimensional principal component analysis combined with k-nearest neighbor (ATLD-kNN and 2DPCA-kNN) and ATLD combined with data-driven soft independent modeling of class analogies (ATLD-DD-SIMCA) were applied to rapid detection of adulteration in saffron. 2DPCA-kNN and ATLD-DD-SIMCA methods were adopted for the classification of chemical EEM data, first with 100% correct classification rate. The content of adulteration of adulterated saffron was predicted by the N-way partial least squares regression (N-PLS) algorithm. In addition, new samples were correctly classified and the adulteration level in adulterated saffron was estimated semi-quantitatively, which verifies the reliability of these models. CONCLUSION: ATLD-DD-SIMCA and 2DPCA-kNN are recommended methods for the classification of pure saffron and adulterated saffron. The N-PLS algorithm shows potential in prediction of adulteration levels. These methods are expected to solve more complex problems in food authenticity. © 2023 Society of Chemical Industry.

Using a 3D Navigation Template to Increase the Accuracy of Thoracic Pedicle Screws in Patients with Scoliosis.

This study compares the accuracy and safety of pedicle screw placement using a 3D navigation template with the free-hand fluoroscopy technique in scoliotic patients. Fifteen scoliotic patients were recruited and divided into a template group (eight cases) and a free-hand group (seven cases). All patients received posterior corrective surgeries, and the pedicle screw was placed using a 3D navigation template or a free-hand technique. After surgery, the positions of the pedicle screws were evaluated using CT. A total of 264 pedicle screws were implanted in 15 patients. Both the two techniques were found to achieve satisfactory safety of screw insertion in scoliotic patients (89.9% vs. 90.5%). In the thoracic region, the 3D navigation template was able to achieve a much higher accuracy of screw than the free-hand technique (75.3% vs. 60.4%). In the two groups, the accuracy rates on the convex side were slightly higher than on the concave side, while no significance was seen. In terms of rotational vertebrae, no significant differences were seen in Grades I or II vertebrae between the two groups. In conclusion, the 3D navigation template technique significantly increased the accuracy of thoracic pedicle screw placement, which held great potential for extensively clinical application.

Anti-interference and non-destructive identification of textile fabrics using front-face excitation-emission matrix fluorescence spectroscopy combined with multi-way chemometrics.

The identification of trace textile fabrics discovered at crime scenes plays a crucial role in the case of forensic investigations. Additionally, in practical situations, fabrics may be contaminated, making identification more challenging. To address the aforementioned issue and promote the application of fabrics identification in forensic analysis, front-face excitation-emission matrix (FF-EEM) fluorescence spectra coupled with multi-way chemometric methods were proposed for the interference-free and non-destructive identification of textile fabrics. Common commercial dyes in the same color range under different materials (cotton, acrylic, and polyester) that cannot be visually distinguished were investigated, and several binary classification models for the identification of dye were established using partial least squares discriminant analysis (PLS-DA). The identification of dyed fabrics in the presence of fluorescent interference was also taken into consideration. In each kind of pattern recognition model mentioned above, the classification accuracy (ACC) of the prediction set was 100%. The alternating trilinear decomposition (ATLD) algorithm was executed to separate mathematically and remove the interference, and the classification model based on the reconstructed spectra attained an accuracy of 100%. These findings indicate that FF-EEM technology combined with multi-way chemometric methods has broad prospects for forensic trace textile fabric identification, especially in the presence of interference.

Front-face excitation-emission matrix fluorescence spectroscopy combined with interpretable deep learning for the rapid identification of the storage year of Ningxia wolfberry.

Ningxia wolfberry stored for many years may be disguised as fresh wolfberry by unscrupulous traders and sold for huge profits. In this work, the front-face excitation-emission matrix (FF-EEM) fluorescence spectroscopy coupled with interpretable deep learning was proposed to identify the storage year of Ningxia wolfberry in a lossless, fast and accurate way. Alternating trilinear decomposition (ATLD) algorithm was used to decompose the three-way data array obtained by Ningxia wolfberry samples, extracting the chemically meaningful information. Meanwhile, a convolutional neural network (CNN) model for the identification of the storage year of Ningxia wolfberry, called EEMnet, was proposed. The model successfully classified wolfberry samples from different storage years by extracting the subtle feature differences of the spectra, and the correct classification rate of the training set, test set and prediction set was more than 98%. In addition, a series of interpretability analyses were implemented to break the "black box" of the deep learning model. These results indicated that the method based on FF-EEM fluorescence spectroscopy combined with EEMnet could quickly and accurately identify the year of Ningxia wolfberry in a green way, providing a new idea for the identification of the storage years of Chinese medicinal materials.

Chemometrics-assisted excitation-emission matrix fluorescence spectroscopy for rapid identification of commercial reconstituted and sweetened grape juices.

As a common fruit juice, grape juice is delicious and nutritious, making it very popular among consumers. However, some illegal manufacturers used shoddy products to lower costs and obtain high profits, which seriously threatens the health and interests of consumers. Hence, this paper proposed excitation-emission matrix (EEM) fluorescence spectroscopy combined with chemometric methods for the rapid identification and classification of commercial grape juices. Spectral characterization of different samples was achieved using the alternating trilinear decomposition (ATLD) algorithm, and chemically meaningful information was obtained and analyzed. Although both reconstituted and sweetened grape juices contain methyl anthranilate (MA) and 2'-aminoacetophenone (o-AAP), the content of MA in sweetened grape juice far exceeds that in reconstituted grape juice, and the MA in sweetened grape juice mainly comes from artificially added grape essence. Then two chemometric methods of hierarchical cluster analysis (HCA) and partial least squares discriminant analysis (PLS-DA) were used for the classification of reconstituted and sweetened grape juices. The results showed that the supervised classification model had a higher correct classification rate (CCR) than the unsupervised classification model, with PLS-DA obtaining 100% CCRs in both training and prediction sets. Therefore, the proposed strategy can be used as a powerful analytical method for the identification and classification of reconstituted and sweetened grape juices and provides a reliable scientific means for ensuring the authenticity and safety of the juice market.

Intelligent analysis of excitation-emission matrix fluorescence fingerprint to identify and quantify adulteration in camellia oil based on machine learning.

Camellia oil (CAO) is a premium edible vegetable oil with medical value and biological activity, but it is susceptible to adulteration. Therefore, the demand for intelligent analysis to decipher the category and proportion of adulterated oil in CAO was the main driver of this work. Excitation-emission matrix fluorescence (EEMF) spectra of 933 vegetable oil samples were characterized by a chemometric method to obtain chemically meaningful information. Authenticity identification models were constructed using four machine learning methods to realize the discrimination of oil species adulterated in CAO mixtures. Meanwhile, quantitative models were established aiming at the fraud of CAO proportion in blended oil. Results showed that the specially constructed CNN obtained the optimal performance when evaluating unseen real-world samples, with a classification accuracy of 95.8% and 92.2%, and mean-absolute quantitative errors between 2.6 and 6.7%. Therefore, EEMF fingerprints coupled with machine learning are expected to provide intelligent and accurate analysis for authenticity detection of CAO.

Species variation in the cartilaginous endplate of the lumbar intervertebral disc.

Backgrounds: Cartilaginous endplate (CEP) plays an essential role in intervertebral disc (IVD) health and disease. The aim was to compare the CEP structure of lumbar IVD and to reveal the detailed pattern of integration between the CEP and bony endplate (BEP) from different species. Methods: A total of 34 IVDs (5 human, 5 goat, 8 pig, 8 rabbit, and 8 rat IVDs) were collected, fixed and midsagittally cut; in each IVD, one-half was used for histological staining to observe the CEP morphology, and the other half was used for scanning electron microscopy (SEM) analysis to measure the diameters and distributions of collagen fibers in the central and peripheral CEP areas and to observe the pattern of CEP-BEP integration from different species. Results: The human, pig, goat, and rabbit IVDs had the typical BEP-CEP structure, but the rat CEP was directly connected with the growth plate. Human CEP was the thickest (896.95 ± 87.71 µm) among these species, followed by pig, goat, rat, and rabbit CEPs. Additionally, the mean cellular density of the rabbit CEP was the highest, which was 930 ± 202 per mm2, followed by the rat, goat, pig, and human CEPs. In all the species, the collagen fiber diameter in the peripheral area was much bigger than that in the central area. The collagen fiber diameters of CEP from the human, pig, goat, and rat were distributed between 35 nm and 65 nm. The BEP and CEP were connected by the collagen from the CEP, aggregating into bundles or cross links with each other to form a network, and anchored to BEP. Conclusions: Significant differences in the thickness, cellular density, and collagen characterization of CEPs from different species were demonstrated; the integration of BEP-CEP in humans, pigs, goats, and rabbits was mainly achieved by the collagen bundles anchoring system, while the typical BEP-CEP interface did not exist in rats.

Chemometrics-enhanced high-performance liquid chromatography-diode array detection strategy to quantify protoberberine alkaloids in varying Coptidis Rhizoma-related medicines.

Quantitation of protoberberine alkaloids is an essential guarantee for efficacy control and medication safety of Coptidis Rhizoma (CR) related medicines. Traditional univariate chromatography faced challenges with co-elution, unknown interferences, and retention time shift when analyzing isomeric analytes in varying sample matrices. We presented a chemometrics-enhanced high-performance liquid chromatography-diode array detection (HPLC-DAD) strategy for simultaneous quantification of six protoberberine alkaloids and processed multi-channels chromatographic-spectral data with four second-order calibration algorithms. Chromatographic conditions were firstly optimized. Four groups of predicted samples were modeled individually with the designed calibration set. Mathematical resolutions were then obtained, and pseudo-univariate regression gave the quantitative concentration of each analyte. Four models were scored on fit, linearity, recovery, and robustness, where alternating trilinear decomposition assisted multivariate curve resolution (ATLD-MCR) exhibited an optimal and stable performance. Besides, the resolved spectra presented high consistency with the actual spectra (r≥0.9993). Limits of quantification (LOQ) fully met the pharmacopoeia stipulation and were 0.17, 0.60, 0.19, 0.74, 0.15, and 0.38 µg mL-1 for columbamine, epiberberine, jatrorrhizine, coptisine, palmatine, and berberine, respectively. The importance of this strategy is to exploit collinearity resolution and additional selectivity that permit accurate quantitation at poor chromatographic resolutions, avoiding individual pretreatment and HPLC optimizations for different samples. This study provides a universal alternative for routine quality assessment of protoberberine alkaloids in CR-related medicines.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry combined with chemometrics to identify the origin of Chinese medicinal materials.

Geographical origin and authenticity are two core factors to promote the development of traditional Chinese medicine (TCM) herbs perception in terms of quality and price. Therefore, they are important to both sellers and consumers. Herein, we propose an efficient, accurate method for discrimination of genuine and non-authentic producing areas of TCM by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Take Atractylodes macrocephala Koidz (AMK) of compositae as an example, the MALDI-TOF MS spectra data of 120 AMK samples aided by principal component analysis-linear discriminant analysis (PCA-LDA), partial least squares discriminant analysis (PLS-DA) and random forest (RF) successfully differentiated Zhejiang province, Anhui province and Hunan province AMK according to their geographical location of origin. The correct classification rates of test set were above 93.3%. Furthermore, 5 recollected AMK samples were used to verify the performance of the classification models. The outcome of this study can be a good resource in building a database for AMK. The combined utility of MALDI-TOF MS and chemometrics is expected to be expanded and applied to the origin traceability of other TCMs.

Analysis of the prevalence, risk factors, and clinical characteristics of osteoporosis in patients with essential hypertension.

BACKGROUND: The present study investigated the prevalence of osteoporosis (OP) among patients with essential hypertension (EH) in the Changchun community and analysed the correlation between EH and OP. METHODS: The study included 425 subjects with EH and 425 age- and sex-matched healthy controls. Bone mineral density (BMD) and serum creatinine (CR) levels were measured, and the subjects' current EH and OP statuses were surveyed to analyse the correlation between EH and OP. RESULTS: The EH group exhibited lower BMD and a higher rate of having OP than the control group, and this difference was statistically significant (p < 0.05). A significant sex difference in the BMD T-score was observed among the subjects (male: - 1.19 ± 1.55, female: - 1.70 ± 1.34). In both the EH group and the control group, the rate of having OP in females was greater than that in males. However, the OP prevalence among subjects with EH varied significantly by age, body weight, fracture history, nocturnal urination frequency, depression and anxiety status, duration of hypertension, and antihypertensive medication use (p < 0.05). Two-way analysis of variance suggested an effect of the interaction between different EH statuses and bone mass conditions on the serum CR values (F = 3.584, p = 0.028, bias η2 = 0.008). CONCLUSIONS: The prevalence of OP and low BMD were significantly higher among subjects with EH than among healthy controls. Additionally, the findings indicate that age, weight, fracture history, nocturnal urination frequency, depression and anxiety, duration of hypertension and antihypertensive drug use may be correlated to having OP in EH subjects, requiring further studies. Moreover, serum CR levels in subjects with different bone mass profiles were strongly influenced by the presence or absence of EH, and the serum CR levels differed significantly with the interaction of these two factors.

Analysis of active compounds and geographical origin discrimination of Atractylodes macrocephala Koidz. by using high performance liquid chromatography-diode array detection fingerprints combined with chemometrics.

In this work, a simple and effective strategy for the determination of 12 active compounds of Atractylodes macrocephala Koidz. (AM) was proposed by using high performance liquid chromatography-diode array detection (HPLC-DAD) combined with alternating trilinear decomposition (ATLD) algorithm. Utilizing the "second-order advantage", three common problems in HPLC could be resolved, namely baseline drifts, peak overlaps, and unknown interferences. 12 compounds were rapidly eluted within 12.5 min, and the average spiked recoveries were 80.8-109.9%. The figures of merit reflected the feasibility of the proposed method. Compared with the results of the traditional univariate calibration method based on HPLC-UV technique, the proposed strategy further verified the reliability and simplicity of the mathematical separation. On this basis, partial least squares-discriminant analysis (PLS-DA) was applied to discriminate 113 AM samples from different geographical origins, and variable importance in projection (VIP) was used to further screen the main differential components that affect the regional division of AM. A series of results show that the AM samples from the three regions have obviously different clustering trends. Overall, the strategy is expected to provide a scientific basis for the modern research of medicinal materials, and it is also conducive to the clinical use and market supervision of AM.

Piecewise direct standardization assisted with second-order calibration methods to solve signal instability in high-performance liquid chromatography-diode array detection systems.

In this paper, in order to solve signal instability of high-performance liquid chromatography-diode array detection (HPLC-DAD) data and maintain the second-order advantage, this work proposed piecewise direct standardization (PDS) assisted with second-order calibration methods to analyze two different complex HPLC-DAD data with signal instability, including simulated HPLC-DAD data and the data of pesticide residues in saffron. Accurate quantitative results of target analytes can be obtained by PDS combined with alternating trilinear decomposition algorithm (ATLD) and alternating trilinear decomposition assisted multivariate curve resolution algorithm (ATLD-MCR) in the presence of signal instability with time shifts and changes of peak shape. Quantitative results of the model after calibration transfer are better than those of the model established by calibration sets and prediction sets with signal instability using ATLD algorithm and ATLD-MCR algorithm under different situations. Meanwhile, t-test was used to judge whether there are significant differences between these quantitative results of models. The performances of MCR-ALS algorithm were compared with that of PDS-ATLD method and PDS-ATLD-MCR method and the proposed methods have greater potential in dealing with the case of signal instability with time shifts and changes of peak shape. In a word, this methodology can reduce the number of calibration samples for recalibration and modeling, improve the efficiency of experiment, conform to the principle of green chemistry, and obtain satisfactory quantitative results in the presence of signal instability with time shifts and changes of peak shape.

Quantitative analysis of carbaryl and thiabendazole in complex matrices using excitation-emission fluorescence matrices with second-order calibration methods.

In this paper, a fast and efficient analytical strategy was proposed that chemometrics assisted with excitation-emission fluorescence matrices was used to quantify carbaryl (CAR) and thiabendazole (TBZ) in peach, soil and sewage. Even if there are serious overlapped peaks and unknown interferences in fluorescence analysis, the second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm can be used to analyze CAR and TBZ in peach, soil and sewage. The recoveries of CAR and TBZ in peach are 110.4% and 99.7% and their standard deviations are lower than 2.1% and 0.3%, respectively. In addition, the accuracy of the method was assessed with figures of merit as well as intra-day and inter-day precision. The limit of detection, the limit of quantitation of CAR and TBZ in peach are 1.2 ng mL-1 and 0.3 ng mL-1, 3.5 ng mL-1 and 0.8 ng mL-1, respectively. And their root-mean-square error of prediction are 17.0 ng mL-1 and 5.0 ng mL-1 and there are high sensitivity and selectivity in this method. Meanwhile, the results obtained by ATLD algorithm were compared with those obtained by the self-weighted alternate trilinear decomposition algorithm (SWATLD) and the parallel factor analysis (PARAFAC) algorithm, and statistical methods such as the t-test, F-test and the elliptic joint confidence region were used to evaluate for analysis. There were no significant differences among these methods. At last, high performance liquid chromatography-fluorescence detector (HPLC-FLD) was used to evaluate the accuracy and reliability of the proposed method. These results are satisfactory and indicate that the proposed method can be used for accurate and rapid determination of pesticides in complex systems.

Geographical origin traceability of traditional Chinese medicine Atractylodes macrocephala Koidz. by using multi-way fluorescence fingerprint and chemometric methods.

Atractylodes macrocephala Koidz. (AM) is an important plant of traditional Chinese medicine (TCM), and its status can be comparable with ginseng in China. The efficacy and quality of AM are closely related to the place of origin. Hence, we proposed a simple and fast strategy to classify AM from different geographical origins by using multi-way fluorescence fingerprint combined with chemometric methods. AM samples with different dilution levels have different fluorescence characteristics, resulting from different content of fluorescence components and chemical microenvironment. Therefore, AM samples were diluted 5-fold, 10-fold, and 20-fold with 40% ethanol aqueous solution to obtain excitation-emission matrix data, and multi-way (three-way and four-way) data arrays were constructed. And then, the fluorescence fingerprints of AM samples were characterized by three-way and four-way parallel factor analysis (PARAFAC). In addition, four pattern recognition methods were used to classify AM from different provinces. The results show that the four-way data array can provide more abundant information than three-way data arrays, so it is more conducive to sample classification. According to the results obtained from the analysis of four-way data array, the correct classification rate (CCR) of the cross-validation and prediction set obtained by partial least squares-discrimination analysis (PLS-DA) were 90.5% and 100%, respectively. To sum up, the proposed method can be regarded as a powerful, feasible, convenient, reliable, and universal classification tool for the classification of AM samples from different provinces and can be used as a promising method to realize the geographical origin traceability of other TCMs.

p53 inhibits CTR1-mediated cisplatin absorption by suppressing SP1 nuclear translocation in osteosarcoma.

Background: Osteosarcoma (OS) is a malignant bone tumor mainly affecting children and young adolescents. Cisplatin is a first-line chemotherapy drug for OS, however, drug resistance severely limits the survival of OS. Nevertheless, cellular factors in cisplatin resistance for OS remain obscure. In this study, the function and potential mechanism of p53 in cisplatin absorption were explored in OS cells. Methods: The CRISPR-Cas9 gene editing technology was performed to obtain p53 gene knock-out U2OS cells. The p53 over-expression 143B cell line was established by lentivirus-mediated virus infection. Moreover, the functions of p53 and CTR1 in cisplatin absorption were assessed by inductively coupled plasma mass spectrometry (ICP-MS) through CTR1 over-expression and knock-down. Further, the DNA binding activity of SP1 on CTR1 gene promoter was determined by dual-luciferase assay and chromatin immunoprecipitation (ChIP) assay. The functional regulation of p53 on SP1 was studied by nucleocytoplasmic separation assay and electrophoretic mobility shift assay (EMSA). The interaction between p53 and SP1 was verified by Co-Immunoprecipitation assay. Results: Under cisplatin treatment, p53 knock-out promoted CTR1 expression and cisplatin uptake, while p53 overexpression inhibited CTR1 expression and cisplatin uptake. Moreover, p53 regulated CTR1 level not by binding to CTR1 promoter directly but by suppressing the nuclear translocation of transcription factor specificity protein 1 (SP1). It was verified that SP1 is directly bound with CTR1 promoter. SP1 overexpression stimulated CTR1 expression, and SP1 knock-down attenuated CTR1 expression. Conclusion: The p53 might function as a negative regulator in CTR1 mediated cisplatin absorption, and the p53-SP1-CTR1 axis is a target for cisplatin resistance.

Rapid determination of sulfamethoxazole and trimethoprim illegally added to health products using excitation-emission matrix fluorescence coupled with the second-order calibration method.

In this work, a simple and fast analytical method based on a self-weighted alternating trilinear decomposition (SWATLD) algorithm coupled with excitation-emission matrix (EEM) fluorescence was developed for the simultaneous determination of sulfamethoxazole (SMZ) and trimethoprim (TMP) illegally added to health products. With the second-order advantage, the proposed method obtained satisfactory results in the presence of peak overlap and unknown interferences. The analysis time for a single sample is only 0.8 minutes. The average spiked recoveries of SMZ and TMP in three health product spiked samples were in the range of 91.0-106.2% and 86.8-107.8%, respectively. The relative standard deviations (RSDs) were lower than 8.6%. In addition, verification parameters including sensitivity (SEN), selectivity (SEL), the limit of detection (LOD), the limit of quantification (LOQ), intra-day precision, and inter-day precision were calculated, and the results show that the proposed method is feasible. The quantitative results of the proposed method were further confirmed by the LC-MS/MS method, which proved that the proposed method was efficient and green for drug-abuse monitoring of SMZ and TMP in health products.

Simultaneous determination of nine tyrosine kinase inhibitors in three complex biological matrices by using high-performance liquid chromatography-diode array detection combined with a second-order calibration method.

An intelligent chemometric second-order calibration method called alternating trilinear decomposition- assisted multivariate curve resolution combined with high-performance liquid chromatography-diode array detection was used for the simultaneous quantification of nine tyrosine kinase inhibitors in three complex biological systems. The method allows simultaneous quantification of the components in different biological matrices without the need for cumbersome pre-treatment steps, complex elution conditions, and complete peak separation. Even with the varying time shift, severe peak overlap, and various unknown interferences, the proposed method can extract pure chromatographic and spectroscopic information for each analyte, while providing accurate qualitative and quantitative results of nine common tyrosine kinase inhibitors in three different biological matrices. All the drugs were eluted in 7 min. The results showed that the nine drugs in each matrix showed good linearity (r > 0.984) in the calibration range with a root mean square error of calibration less than 0.9 µg/mL. The average spiked recoveries of the target analytes were all in the range of 83.4-110.0%, with standard deviations less than 9.0%. Finally, the classical method was used to validate the proposed method. In comparison to the traditional method, the proposed strategy is accuracy, simultaneous, and interference-free.

Fast identification of the geographical origin of Gastrodia elata using excitation-emission matrix fluorescence and chemometric methods.

Geographical origin is an important factor affecting the quality of traditional Chinese medicine. In this paper, the identification of geographical origin of Gastrodia elata was performed by using excitation-emission matrix fluorescence and chemometric methods. Firstly, excitation-emission matrix (EEM) fluorescence spectra of Gastrodia elata samples from different geographical origins were obtained. And then three chemometric methods, including multilinear partial least squares discriminant analysis (N-PLS-DA), unfold partial least squares discriminant analysis (U-PLS-DA), and k-nearest neighbor (kNN) method, were applied to build discriminant models. Finally, 45 Gastrodia elata samples could be differentiated from each other by these classification models according to their geographical origins. The results showed that all models obtained good classification results. Compared with the N-PLS-DA and U-PLS-DA, kNN got more accurate and reliable classification results and could identify Gastrodia elata samples from different geographical origins with 100% accuracy on the training and test set. Therefore, the proposed method was available for easily and quickly distinguishing the geographical origin of Gastrodia elata, which can be considered as a promising alternative method for determining the geographic origin of other traditional Chinese medicines.

Three efficient chemometrics assisted fluorimetric detection methods for interference-free, rapid, and simultaneous determination of ibrutinib and pralatrexate in various complicated biological fluids.

In this study, a series of green, interference-free fluorimetric detection methods of the excitation-emission matrix coupled with the second-order calibration methods were proposed for the determination of ibrutinib and pralatrexate in various complicated biological fluids. The second-order advantage of the proposed method can overcome the problem of poor selectivity caused by the wide spectra of the fluorescence method. Even in the presence of uncalibrated interferences and severe peak overlap, the signal of pure substance and accurate quantitative results were still obtained. The average recoveries of the three methods were 94.5-104.9% for Alternating Trilinear Decomposition (ATLD) algorithm, 95.5-105.8% for Alternating Normalization Weighted Error (ANWE) algorithm and 94.4-105.7% for Parallel Factor Analysis (PARAFAC) algorithm, respectively. For ATLD, ANWE and PARAFAC, the relative standard deviations (RSD) were lower than 9.2%, 6.8% and 9.2%, and the RMSEPs were less than 8.1, 8.4 and 8.6 ng mL-1, respectively. In addition, the elliptic joint confidence region (EJCR) was adopted to further prove the accuracy of the three methods. The results showed that the three methods can accurately be quantified without significant difference. Good figures of merit parameters were also obtained. Among them, the limit of detection (LOD) and limit of quantification (LOQ) of ibrutinib and pralatrexate were in the range of 0.11-0.76 ng mL-1 and 0.21-1.12 ng mL-1, respectively, which were lower than the corresponding blood concentrations. These results indicate that the proposed method provides a promising, alternative and universal analysis strategy for clinical drug monitoring.