A user DNS fingerprint dataset

Using a user DNS fingerprint allows one to identify a specific network user regardless of the knowledge of his IP address. This method is proper, for example, when examining the behavior of a monitored network user in more depth. In contrast to other studies, this work introduces a dataset for possible user identification based only on the knowledge of its DNS fingerprint created from the previously sent DNS queries. We created a large dataset from the real network traffic of a metropolitan Internet service provider. The dataset was created from 2.3 billion DNS queries representing 6.2 million different domain names. The data collection took place over three months from 12/2023 to 02/2024. The dataset contains a detailed user activity description in the sense of overall daily activity statistics and detailed 24 h activity statistics. Each dataset record contains a list of 1137 classification attributes. The absolutely unique feature of this data set is the classification of user activity based on categories of content accessed by a user. The new dataset can be used for the creation of machine learning models, allowing the identification of a specific user without direct knowledge of their IP addresses or additional network location information. The dataset can also serve as a reference dataset for the creation of DNS fingerprints of users.

A study for quality evaluation of Lysimachiae herba from different origins based on fingerprint-activity relationship modeling and multi-component content determination

ETHNOPHARMACOLOGICAL RELEVANCE

Lysimachiae Herba (LH), called Jinqiancao in Chinese, is a commonly used traditional Chinese medicine in clinical practice. Doctors in the Qing Dynasty recorded that it tastes bitter, sour, and slightly cold, and it belongs to the liver, gallbladder, kidney, and bladder meridians. It has the effects of removing dampness and jaundice, eliminating gallstones, and reducing blood stasis. Because of its potent pharmacological effects, it is extensively utilized in the treatment of hepatobiliary and urinary system stones, jaundice, hepatitis, and cholecystitis. Although LH is included in "Sichuan authentic Chinese herbal medicine records", the quality of it from different origins still lacks reliable evaluation methods, which is difficult to reflect the high quality of LH from Sichuan.

AIMS OF THE STUDY

This study aimed to establish a fingerprint-activity relationship model between the fingerprint of LH and its protective effect on cholestatic liver injury, and to evaluate the quality of LH from Sichuan and Guizhou by multivariate statistical analysis.

MATERIALS AND METHODS

20 batches of LH samples were collected from Sichuan and Guizhou. Characteristic fingerprints of samples were established by UHPLC-Triple TOF-MS/MS and the chemical pattern recognition analysis was carried out by HCA. Then, a rat model of cholestatic liver injury was established by intragastric administration of ANIT. Combined with the common peak information of fingerprint and pharmacodynamic index results, GCA and BCA were used to screen the efficacy markers. Finally, based on UHPLC-QTRAP-MS/MS, the content of efficacy markers was simultaneously determined, and the overall quality of LH from two origins was evaluated by PCA and TOPSIS.

RESULTS

In the fingerprint of 20 batches of LH, 15 common peaks were identified in the negative ion mode, and the similarity was between 0.887 and 0.981. Pharmacological results showed that, compared with the control group, the content of AST, ALT, ALP, TBA, TBIL, and MDA in serum increased, and the content of GSH and SOD activity decreased after 48 h of ANIT administration. In addition, compared to the model group, different doses of LH from the two origins could decrease the serum levels of AST, ALT, ALP, TBA, TBIL, and MDA, raise the levels of GSH and SOD activity, reduce the infiltration range of inflammatory cells, and improve the cholestatic liver injury in rats. Among them, the pharmacodynamic indices of the SCHD group were significantly better. GCA and BCA showed that a total of 7 constituents related to the efficacy were screened, which were proanthocyanidin B1, ferulic acid, hyperoside, astragalin, nicotiflorin, afzelin, and kaempferol. Besides, the content of 7 active constituents in samples from Sichuan was higher than that from Guizhou, indicating that the quality of samples from Sichuan may be better, consistent with the result of the pharmacological experiment.

CONCLUSION

The quality and efficacy of LH from different origins were stable, and all of them had protective effects on cholestatic liver injury in rats. The method established in this study is accurate and reliable, and it can be used to comprehensively evaluate the internal quality of LH.

Fingerprint analysis of dang-gui-Si-Ni decoction and its anticoagulant activity in vivo-in vitro

ETHNOPHARMACOLOGICAL RELEVANCE

Dang-Gui-Si-Ni (DGSN) decoction is a classic prescription in the clinical practice of traditional Chinese Medicine (TCM). DGSN decoction is often used to relieve symptoms of cold coagulation and blood stasis recorded by Treatise on Febrile Diseases (Shang Han Lun) and treat Raynaud's disease, dysmenorrhea, arthritis, migraine in TCM clinic. Accumulated evidences have suggested that this diseases are related to microcirculation disturbance. However, the anticoagulant activity and underlying mechanisms of DGSN decoction responsible for the therapeutic not well understood.

AIM OF THE STUDY

The fingerprint and anticoagulant activity in vivo-in vitro of DGSN decoction were evaluated to strengthen the quality control and activity study of formulas.

MATERIALS AND METHODS

The chemical components of DGSN decoction were analyzed by HPLC and its fingerprint similarity were evaluated by "Chinese Medicine Chromatographic Fingerprint Similarity Evaluation Software (2012 Edition)". The anticoagulant activity of DGSN decoction was assessed by measuring four coagulation factors (PT, TT, APTT, FIB) in vitro. Zebrafish thrombosis model induced by punatinib was established to evaluate the activity of improving microvascular hemodynamics in vivo. Quantitative real-time polymerase chain reaction (q-PCR) were adopted to compare the changes in the RNA expression levels of coagulation factor II (FII), VII (FVII), IX (FIX) and X (FX) in zebrafish thrombosis model.

RESULTS

The fingerprint similarity evaluation method of DGSN decoction was established. The results showed that 18 samples had higher similarity (S1-S18 > 0.878). Pharmacodynamic results showed that DGSN decoction could extend PT, TT and APTT, and reduce FIB content in vitro. Meanwhile, it markedly enhanced the cardiac output and blood flow velocity at low dosage (500 μg mL-1) in vivo. q-PCR data demonstrated that DGSN decoction (500 μg mL-1) could downregulate the RNA expression of FII, FVII, FIX and FX. Interestingly, there were a bidirectional regulation of FII, FIX and FX in a certain concentration range. In general, DGSN decoction can significantly improve hemodynamics and downregulate coagulation factors, and the results were consistent both in vitro - in vivo.

CONCLUSION

The fingerprint study provide a new perspective for improving the quality control of DGSN decoction. DGSN decoction possess anticoagulant activity by regulating multiple coagulation factors simultaneously. Thus, it has the potential to develop into the novel raw material of anticoagulant drugs.

Effectiveness of molecular fingerprints for exploring the chemical space of natural products

Natural products are a diverse class of compounds with promising biological properties, such as high potency and excellent selectivity. However, they have different structural motifs than typical drug-like compounds, e.g., a wider range of molecular weight, multiple stereocenters and higher fraction of sp3-hybridized carbons. This makes the encoding of natural products via molecular fingerprints difficult, thus restricting their use in cheminformatics studies. To tackle this issue, we explored over 30 years of research to systematically evaluate which molecular fingerprint provides the best performance on the natural product chemical space. We considered 20 molecular fingerprints from four different sources, which we then benchmarked on over 100,000 unique natural products from the COCONUT (COlleCtion of Open Natural prodUcTs) and CMNPD (Comprehensive Marine Natural Products Database) databases. Our analysis focused on the correlation between different fingerprints and their classification performance on 12 bioactivity prediction datasets. Our results show that different encodings can provide fundamentally different views of the natural product chemical space, leading to substantial differences in pairwise similarity and performance. While Extended Connectivity Fingerprints are the de-facto option to encoding drug-like compounds, other fingerprints resulted to match or outperform them for bioactivity prediction of natural products. These results highlight the need to evaluate multiple fingerprinting algorithms for optimal performance and suggest new areas of research. Finally, we provide an open-source Python package for computing all molecular fingerprints considered in the study, as well as data and scripts necessary to reproduce the results, at https://github.com/dahvida/NP_Fingerprints .

Membranes are functionalized by a proteolipid code

Membranes are protein and lipid structures that surround cells and other biological compartments. We present a conceptual model wherein all membranes are organized into structural and functional zones. The assembly of zones such as receptor clusters, protein-coated pits, lamellipodia, cell junctions, and membrane fusion sites is explained to occur through a protein-lipid code. This challenges the theory that lipids sort proteins after forming stable membrane subregions independently of proteins.

Identification of Adulteration of Flaxseed Oil From QINGHAI Area Using GC-MS Profiling of Phytosterol Composition and Chemometrics

Flaxseed oil is an important source of vegetable oil with a polyunsaturated fatty acid. It is significant to establish a method to quickly identify adulterated flaxseed oil. In the present study, the qualitative and quantitative analysis of phytosterol of flaxseed oil from different varieties and different production areas in the Qinghai area was first performed by gas chromatography-mass spectrometry (GC-MS) and the phytosterol standard profile of flaxseed oil was established. Then, a combination of similarity evaluation and cluster analysis was used to distinguish pure flaxseed oil from flaxseed oil adulterated with concentrations of 10-50% rapeseed oil, peanut oil, sunflower oil, and sesame oil, and discriminant analysis was used to identify the types of adulterated flaxseed oil. The results showed that similarity evaluation combined with cluster analysis can distinguish pure and adulterated flaxseed oil when the concentration of the adulterant was greater than 10%. Discriminant analysis models accurately identified the types of adulterating oil in flaxseed oil when the concentration of rapeseed, peanut, or sunflower oil was greater than 20%, and that of sesame oil was greater than 30%. This study shows that the determination of the phytosterol composition and chemometrics is a valuable tool to evaluate the purity of flaxseed oil.

Graphical Discrimination of New Zealand Honey from International Honey Using Elemental Analysis

This study investigated the potential of utilising the elemental fingerprinting of honey to differentiate New Zealand (NZ) honey from that of international origin. Twenty elements were analysed by ICP-MS in 352 honeys from 34 various countries. Of these, 323 honeys (245 New Zealand honeys, 78 international) and two subsets of data (NZ and European origin, n = 306, and, NZ and Denmark/Germany, n = 280) were visualised using principal component analysis (PCA). For the NZ/Europe subset, 42.2% of data was explained in the first two principal components. Statistical classification rules were also derived using linear discriminant analysis (LDA) and decision tree analysis. Various combinations of elements were explored for classification, considering the effect of soil-derived elements and those from anthropogenic sources. A high degree of accuracy (at least 90%) for the characterisation of New Zealand honey was observed for all statistical models, showing the robustness of these analyses. When using decision tree analysis to distinguish New Zealand samples from international samples, a tree with five terminal nodes (using Cs, Ba and Rb) was created with 92.4% accuracy. This work has demonstrated that elemental fingerprints of honey are a promising tool for categorising New Zealand honey from other geographical locations.

Thermal utilization techniques and strategies for secondary aluminum dross: A review

Secondary aluminum ash (SAD) disposal is challenging, particularly in developing countries, and presents severe eco-environmental risks. This paper presents the treatment techniques, mechanisms, and effects of SAD at the current technical-economic level based on aluminum ash's resource utilization and environmental properties. Five recovery techniques were summarized based on aluminum's recoverability in SAD. Four traditional utilization methods were outlined as per the utilization of alumina in SAD. Three new utilization methods of SAD were summarized based on the removability (or convertibility) of aluminum nitride in SAD. The R-U-R (recoverability, utilizability, and removability) theory of SAD was formed based on several studies that helped identify the fingerprint of SAD. Furthermore, the utilization strategies of SAD, which supported the recycling of aluminum ash, were proposed. To form a perfect fingerprint database and develop various relevant techniques, future research must focus on an extensive examination of the characteristics of aluminum ash. This research will be advantageous for addressing the resource and environmental challenges of aluminum ash.

Distribution of PCDD/Fs and PCBs at different locations in a circulating fluidised bed municipal solid waste incinerator

This study investigates a circulating fluidised bed (CFB) incineration plant to examine the concentrations and fingerprints of polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), and biphenyls (PCBs) at five locations downstream of the post-combustion zone. Sampling encompassed both flue gas and ash, spanning from the high-temperature superheater to the outlet of the baghouse filter, thus covering a wide range of flue gas temperatures. The analysis reveals a continuous increase in PCDD/F and PCB concentrations in the flue gas from the superheater to the inlet of the air pollution control system (APCS). The maximum concentrations observed were 75.8 ng/Nm3 for PCDDs, 219 ng/Nm3 for PCDFs, and 763 ng/Nm3 for PCBs. These values represent 9.14, 11.5, and 6.37 times their respective concentrations at the outlet of the high-temperature superheater. Concurrently, the levels of PCDD/Fs and dioxin-like PCBs (dl-PCBs) in the ash steadily increased along the cooling path of the flue gas within the plant. Comparing dl-PCBs to the total amount of 209 PCB congeners, it was evident that dl-PCBs exhibited a trend more akin to that of PCDD/Fs. A robust linear correlation was observed between dl-PCBs and PCDD/Fs (R2 = 0.99, p < 0.001), surpassing that between PCBs and PCDD/Fs (R2 = 0.92, p < 0.01), suggesting that dl-PCBs share closer formation pathways with PCDD/Fs. Additionally, elemental composition analysis of fly ash samples aimed to explore potential links between fly ash characteristics and PCDD/F and PCB formation. The Cl/S ratio increased from 1.58 to 5.13 with decreasing flue gas temperature. Principal component analysis (PCA) was employed to visualise the concentrations of PCDD/Fs and PCBs in the flue gas alongside elemental contents in the fly ash. With the exception of PCBs in ash, all other PCDD/Fs and PCBs in fly ash exhibited positive correlations with both carbon (C) and chlorine (Cl). Furthermore, a positive relationship between C/Cl and PCDD/Fs-PCBs in fly ash implies that fly ash serves as the primary reaction surface for dioxin generation during low-temperature heterogeneous catalytic reactions.

Prediction of free radical reactions toward organic pollutants with easily accessible molecular descriptors

Machine learning (ML) is becoming an efficient tool for predicting the fate of aquatic contaminants owing to the preponderance of big data. However, whether ML can "learn" the differences in reactivity among different free radicals has not yet been tested. In this work, the effectiveness of combining ML algorithms with molecular fingerprints to predict the reactivity of three free radicals was evaluated. First, a dataset containing 211 organic pollutants and their respective rate constants with the carbonate radical (CO3•-) was used to develop predictive models using both linear regression and ML methods. The use of topological atomic alignment information, in the form of the molecular access system (MACCS) and Morgan Fingerprint, and the electronic structure features (energy levels of the lowest unoccupied and highest occupied molecular orbitals, ELUMO and EHOMO, and the energy gap between ELUMO and EHOMO) gave satisfactory predictive performances (ML model with Random Forest algorithm with MACCS: RMSEtest = 0.787; linear regression model with energy levels: RMSEtest = 0.641). Additionally, the model interpretation correctly described that the key reactivity features for CO3•- were relatively close to those for SO4•- rather than those for •OH. These results suggest that combination of ML algorithms with easily accessible molecular fingerprints would be a powerful tool to accurately predict the radical reactions towards organic compounds.

Metabolomic Fingerprint Assay in Zebrafish Embryos

In order for new drugs to enter the market, extensive studies are needed to examine toxic effects. Among others, teratogenicity studies are of paramount importance. Of even higher importance is to gain knowledge on the biological responses that take place upon drug exposure, so as to have a better understanding of the molecular mechanisms that govern developmental changes. Metabolomics is the research field that studies the changes in the chemical composition of metabolites contained within cells. Conducting metabolomics studies results in valuable information. Zebrafish is a vertebrate model organism that bridges in vivo assays and in vivo studies. In this chapter, we propose a metabolomic fingerprint assay for the study of metabolic changes in zebrafish embryos upon exposure to various drugs. The metabolome of zebrafish is extracted, and the 1H-NMR spectrum is recorded. Using open-access metabolomic databases, a list of tentative metabolites is retrieved. The presence of the tentative metabolites is further confirmed by UHPLC-HRMS. Ultimately, after a metabolic pathway analysis, the metabolic network is revealed and useful conclusions can be drawn.

Label-free SERS for rapid identification of interleukin 6 based on intrinsic SERS fingerprint of antibody‑gold nanoparticles conjugate

A label-free surface-enhanced Raman scattering (SERS) was designed for sensitive detection of interleukin-6 (IL-6). The sensing element composed of anti-IL-6 antibodies adsorbed on the surface of spherical gold nanoparticles (AuNPs) as SERS-active surface. The principle of detection was probing antibody conformational changes using its intrinsic SERS fingerprint after binding to IL-6. Comparison of SERS spectra of antibody before and after binding to IL-6 showed that secondary structure of antibody does not change upon binding to IL-6. Vibrational information from disulfide bonds ν(SS) in antibody structure indicated some changes of geometry around SS bridges as a consequence of the immunocomplex formation. Transmission electron microscopy (TEM) and UV-Vis spectroscopy were used to confirm AuNPs conjugation with antibody as well as IL-6 binding to antibody on the surface of AuNPs. The SERS-based immunoassay showed a wide linear range (2.0-1000 pg mL-1) and a high sensitivity with a limit of detection (LOD) as low as 0.91 pg mL-1 (0.04 pM) without using any extrinsic Raman label. UV-Vis spectroscopy was employed as a conventional method for IL-6 detection based on observation of any change in the position of localized surface plasmon resonance (LSPR) band of AuNPs-antibody conjugates with LOD of 10 ng mL-1.

Improving quality of analysis by suppression of unwanted signals through band-selective excitation in NMR spectroscopy for metabolomics studies

INTRODUCTION

Nuclear Magnetic Resonance (NMR) spectroscopy stands as a preeminent analytical tool in the field of metabolomics. Nevertheless, when it comes to identifying metabolites present in scant amounts within various types of complex mixtures such as plants, honey, milk, and biological fluids and tissues, NMR-based metabolomics presents a formidable challenge. This predicament arises primarily from the fact that the signals emanating from metabolites existing in low concentrations tend to be overshadowed by the signals of highly concentrated metabolites within NMR spectra.

OBJECTIVES

The aim of this study is to tackle the issue of intense sugar signals overshadowing the desired metabolite signals, an optimal pulse sequence with band-selective excitation has been proposed for the suppression of sugar's moiety signals (SSMS). This sequence serves the crucial purpose of suppressing unwanted signals, with a particular emphasis on mitigating the interference caused by sugar moieties' signals.

METHODS

We have implemented this comprehensive approach to various NMR techniques, including 1D 1H presaturation (presat), 2D J-resolved (RES), 2D 1H-1H Total Correlation Spectroscopy (TOCSY), and 2D 1H-13C Heteronuclear Single Quantum Coherence (HSQC) for the samples of dates-flesh, honey, a standard stock solution of glucose, and nine amino acids, and commercial fetal bovine serum (FBS).

RESULTS

The outcomes of this approach were significant. The suppression of the high-intensity sugar signals has considerably enhanced the visibility and sensitivity of the signals emanating from the desired metabolites.

CONCLUSION

This, in turn, enables the identification of a greater number of metabolites. Additionally, it streamlines the experimental process, reducing the time required for the comparative quantification of metabolites in statistical studies in the field of metabolomics.

Ilm-NMR-P31: an open-access 31P nuclear magnetic resonance database and data-driven prediction of 31P NMR shifts

This publication introduces a novel open-access 31P Nuclear Magnetic Resonance (NMR) shift database. With 14,250 entries encompassing 13,730 distinct molecules from 3,648 references, this database offers a comprehensive repository of organic and inorganic compounds. Emphasizing single-phosphorus atom compounds, the database facilitates data mining and machine learning endeavors, particularly in signal prediction and Computer-Assisted Structure Elucidation (CASE) systems. Additionally, the article compares different models for 31P NMR shift prediction, showcasing the database's potential utility. Hierarchically Ordered Spherical Environment (HOSE) code-based models and Graph Neural Networks (GNNs) perform exceptionally well with a mean squared error of 11.9 and 11.4 ppm respectively, achieving accuracy comparable to quantum chemical calculations.

Identification of Different Varieties of Oil Peony Seeds Combining ICP-MS with Chemometrics and Assessment of Associated Health Risk

Peony seed is an excellent oil crop, and peony seed oil is rich in unsaturated fatty acids needed by the human body. In this study, inductively coupled plasma mass spectrometry (ICP-MS), fingerprint, and chemometrics, the correlation between the content of inorganic elements in oil peony seeds, their origins, and varieties were investigated. Meanwhile, estimated daily intake (EDI), target hazard quotient (THQ), hazard index (HI), and carcinogenic risks (CR) were combined to evaluate the comprehensive health risks of heavy metals in peony seed oil. The results showed that the difference in the content of inorganic elements could identify the varieties of oil peony seeds. Sr, K, Ca, V, Al, Fe, Cu, Ba, As, Ga, Co, and Rb were the characteristic inorganic elements that played a role in identification. In addition, The THQs and HIs (< 1) for non-carcinogenic elements indicated no risk. The CRs indicated that the carcinogenic harm was negligible. The study concluded that three varieties of peony seed oil would not pose any health hazard. It provided an effective comprehensive method for the identification of oil peony seeds and predicted the potential health risks of edible peony seed oil, providing a reference for the development and consumption of peony seed oil food.

Clustering of Tadalafil API Samples According to their Manufacturer in the Context of API Falsification Detection

This paper reports the results of the active pharmaceutical ingredient (API) fingerprint study, organised by the General European Official Medicines Control Laboratory Network (GEON), on tadalafil. A classical market surveillance study, evaluating compliance to the European Pharmacopoeia, was combined with a fingerprint study, the latter to obtain characteristic data for the different manufacturers, allowing the network laboratories to conduct authenticity tests for future samples, as well as to detect substandard and falsified samples. In total, 46 tadalafil API samples from 13 different manufacturers were collected. For all samples fingerprint data was collected through analysis of impurities and residual solvents, mass spectrometric screening, X-ray powder diffraction and proton nuclear magnetic resonance (1H-NMR). Chemometric analysis revealed that all manufacturers could be characterised based on the impurity, residual solvent and 1H-NMR data. Future suspicious samples in the network will therefore be analysed with these techniques in order to attribute the sample to one of the manufacturers. If the sample cannot be attributed, a more profound investigation will be necessary to reveal the origin of the sample. In cases where the suspect sample is claimed to be from one of the manufacturers included in this study, analysis can be limited to the test distinguishing that manufacturer.

Prediction of organic compound aqueous solubility using machine learning: a comparison study of descriptor-based and fingerprints-based models

A reliable and practical determination of a chemical species' solubility in water continues to be examined using empirical observations and exhaustive experimental studies alone. Predictions of chemical solubility in water using data-driven algorithms can allow us to create a rationally designed, efficient, and cost-effective tool for next-generation materials and chemical formulations. We present results from two machine learning (ML) modeling studies to adequately predict various species' solubility using data for over 8400 compounds. Molecular-descriptors, the most used method in previous studies, and Morgan fingerprint, a circular-based hash of the molecules' structures, were applied to produce water solubility estimates. We trained all models on 80% of the total datasets using the Random Forest (RFs) technique as the regressor and tested the prediction performance using the remaining 20%, resulting in coefficient of determination (R2) test values of 0.88 and 0.81 and root-mean-square deviation (RMSE) test values 0.64 and 0.80 for the descriptors and circular fingerprint methods, respectively. We interpreted the produced ML models and reported the most effective features for aqueous solubility measures using the Shapley Additive exPlanations (SHAP) and thermodynamic analysis. Low error, ability to investigate the molecular-level interactions, and compatibility with thermodynamic quantities made the fingerprint method a distinct model compared to other available computational tools. However, it is worth emphasizing that physicochemical descriptor model outperformed the fingerprint model in achieving better predictive accuracy for the given test set.

Bloom filters for molecules

Ultra-large chemical libraries are reaching 10s to 100s of billions of molecules. A challenge for these libraries is to efficiently check if a proposed molecule is present. Here we propose and study Bloom filters for testing if a molecule is present in a set using either string or fingerprint representations. Bloom filters are small enough to hold billions of molecules in just a few GB of memory and check membership in sub milliseconds. We found string representations can have a false positive rate below 1% and require significantly less storage than using fingerprints. Canonical SMILES with Bloom filters with the simple FNV (Fowler-Noll-Voll) hashing function provide fast and accurate membership tests with small memory requirements. We provide a general implementation and specific filters for detecting if a molecule is purchasable, patented, or a natural product according to existing databases at https://github.com/whitead/molbloom .

Synergetic effects of boron nitride with waste zirconia: Evaluation of instantaneous fingerprint detection and mechanical properties for biomedical applications

Herein, present study mainly focuses on the synthesis and characterizations of boron nitride reinforced waste zirconia (wZrO2) with different concentrations. Composites were prepared via a scalable solid-state reaction method. Various physical parameters such as density, ionic concentration, polaron radius, and field strength were evaluated. XRD results reveal crystalline nature with a major phase of tetragonal zirconia and as boron nitride is reinforced, the tetragonal transforms into a monoclinic zirconia. Interconnected spherical grains and nanosheets were observed using FESEM. Mechanical characterizations revealed the highest compressive strength of 266 MPa. The latent fingerprints were visualized using a composite on different surfaces, implementing the powder dusting and solution techniques. MTT assay was performed and revealed good biocompatible nature. These results reveal that composite is suitable for fabrication of bioceramics with acceptable mechanical and biological performances. The composite can also be utilized for latent fingerprint detection in forensic science.

Reduced clinical connectome fingerprinting in multiple sclerosis predicts fatigue severity

BACKGROUND

Brain connectome fingerprinting is progressively gaining ground in the field of brain network analysis. It represents a valid approach in assessing the subject-specific connectivity and, according to recent studies, in predicting clinical impairment in some neurodegenerative diseases. Nevertheless, its performance, and clinical utility, in the Multiple Sclerosis (MS) field has not yet been investigated.

METHODS

We conducted the Clinical Connectome Fingerprint (CCF) analysis on source-reconstructed magnetoencephalography signals in a cohort of 50 subjects: twenty-five MS patients and twenty-five healthy controls.

RESULTS

All the parameters of identifiability, in the alpha band, were reduced in patients as compared to controls. These results implied a lower similarity between functional connectomes (FCs) of the same patient and a reduced homogeneity among FCs in the MS group. We also demonstrated that in MS patients, reduced identifiability was able to predict, fatigue level (assessed by the Fatigue Severity Scale).

CONCLUSION

These results confirm the clinical usefulness of the CCF in both identifying MS patients and predicting clinical impairment. We hope that the present study provides future prospects for treatment personalization on the basis of individual brain connectome.

Surface-enhanced Raman imaging through sprayed probes for the application in chemical visualization of methamphetamine within fingerprints

For fingerprint-involved forensic investigations, cyanoacrylates and inorganic nanophosphors are mostly used for fingerprint visualization. However, methods to simultaneously report fingerprint images and the corresponding specific chemical information have yet to be realized. In this work, chemical visualization of the analytes in fingerprints is achieved through surface-enhanced Raman spectroscopy (SERS) measurements with the aid of spray-dispersed gold nanorods (AuNRs). The optimal coverage of AuNRs was studied by theoretical simulations and experimental operations. A rapid sampling of fingerprints with the chemical of interest was developed by tuning the spray parameters. In particular, the SERS imaging of methamphetamine in fingerprint latent was attempted by addressing the SERS spectral features of methamphetamine. This chemical visualization method reflects both the graphical and chemical characteristics of fingerprints in a single batch measurement, in which methamphetamine can be detected and mapped at the concentration of 10^-5 M. The data processing approach was also modified by employing relevant logical judgments. The improved SERS images with sharpened patterns of fingerprints were obtained by involving the scored multi-peak judgments.

Spectralprint techniques coupled with chemometric tools for vinegar classifications

Vinegar is a versatile product used for food preservation, cooking, healthcare, and cleaning. In this study, 80 vinegar of different raw materials, aging time, and for the first time by the agronomic method of raw material cultivation were classified by spectralprint techniques with chemometrics. Datasets were obtained by proton nuclear magnetic resonance (¹H NMR), Fourier transforms mid-infrared (FT-IR), near-infrared (NIR), and ultraviolet-visible (UV-vis); then evaluated by common dimension (ComDim) and partial least squares-discriminant analysis (PLS-DA). NMR with PLS-DA had the best prediction performance compared to other techniques, with accuracy values between 92.3 and 100 %, followed by FT-IR and UV-vis of 80.8 and 96.0 % and NIR between 69.2 and 84.0 %. The results indicated that the classification of vinegar according to the agronomic cultivation method is more complex than aging time or raw material. However, any of these spectralprint techniques have demonstrated that they can be used in the classification of vinegar.

Building a library of source samples for sediment fingerprinting - Potential and proof of concept

PURPOSE

Sediment fingerprinting of fluvial targets has proven useful to guide conservation management and prioritize sediment sources for Federal and State supported programs in the United States. However, the collection and analysis of source samples can make these studies unaffordable, especially when needed for multiple drainage basins. We investigate the potential use of source samples from a basin with similar physiography (using samples from one of a "pair" to evaluate samples from the other) or combined from multiple basins (a "library").

METHODS

Source samples from eight basins across six ecoregions were harvested from existing, published studies. Individual source samples were fingerprinted using a mixing model derived from source samples from other basins. The ability to identify source category was evaluated both as part of source verification and by classifying source samples as "targets."

RESULTS

Approximately half of cropland samples were identified as targets, both as pairs and with the multi-basin source dataset, indicating that cropland samples could be shared for basins in similar ecoregions and be combined for larger stream systems. Streambank samples were better identified with the multi-basin analysis relative to the pairs, and those from mixed land-use basins improved this differentiation except for samples from basins with a dominant land-use type. Inconsistent identification of pasture samples highlighted the need for local samples. Inconsistent identification of forest samples indicated that upland- and riparian-forest samples are distinct. Road samples were identified as both sources and targets, and other source types were rarely apportioned as road: these may have the best potential to supplement local source samples. This source-sample library was then used to improve the accuracy of sediment-source apportionment for a previously studied basin.

CONCLUSION

Ultimately, the source verification process already used in individual basin studies to evaluate the accuracy of sediment-fingerprinting apportionments was useful for determining how to supplement local source samples with those from other basins. This study shows that supplementing local source samples with those from basins with similar physiography has the potential to both improve fingerprinting accuracy and decrease the cost of this type of study.

Assessment and Correlation between Dactyloscopy and Behavior of Children Undergoing Dental Treatment: A Cross-sectional Study

Aim

To assess and correlate dactyloscopy and behavior of children undergoing dental treatment.

Materials and methods

A total of 30 children aged 4-8 years who needed at least one restoration without administration of local anesthesia were included. Two examiners recorded the behavior of the child as per Frankl's behavior rating scale and after the treatment, the subjects' fingerprints were taken using an ink pad and white paper. The data were analyzed using Statistical Package for the Social Sciences (SPSS) versions 23 and a Chi-squared test was carried out (p < 0.05).

Results

The loop type fingerprint had the highest frequency, while the archtype had the lowest. The child's behavior differed greatly (p < 0.05) based on dermatoglyphic characteristics, with the loop pattern being seen in cooperative children and the whorl pattern in uncooperative children.

Conclusion

There is a positive correlation between fingerprint type and children's dental care.

Clinical significance

Dactyloscopy can be used to determine the behavior of children coming for dental treatment and hence help in their management.

How to cite this article

Janiani P, Subramanian EMG. Assessment and Correlation between Dactyloscopy and Behavior of Children Undergoing Dental Treatment: A Cross-sectional Study. Int J Clin Pediatr Dent 2023;16(3):444-447.

Microbes in fingerprints: A source for dating crime evidence?

Interest in the human microbiome has grown in recent years because of increasing applications to biomedicine and forensic science. However, the potential for dating evidence at a crime scene based upon time-dependent changes in microbial signatures has not been established, despite a relatively straightforward scientific process for isolating the microbiome. We hypothesize that modifications in microbial diversity, abundance, and succession can provide estimates of the time a surface was touched for investigative purposes. In this proof-of-concept research, the sequencing and analysis of the 16 S rRNA gene from microbes present in fresh and aged latent fingerprints deposited by three donors with pre- and post-washed hands is reported. The stability of major microbial phyla is confirmed while the dynamics of less abundant groups is described up to 21 days post-deposition. Most importantly, a phylum is suggested as the source for possible biological markers to date fingerprints: Deinococcus-Thermus.

An effective fingerprint orientation field estimation method using differential values of grayscale intensity

Fingerprint orientation field (OF) estimation is important for basic fingerprint image processing and impacts the accuracy of fingerprint image enhancements, such as Gabor filters. In this article, we introduce an OF estimation algorithm based on differential values of grayscale intensity and examine the accuracy and reliability of the proposed algorithm by applying it to fingerprint images processed using Gaussian blurring and the Gaussian white noise process. The experimental results indicate that the OF estimation reliability of the proposed algorithm is higher than the gradient-based method and the power spectral density (PSD) based method in low quality fingerprints. The proposed algorithm is especially useful in noisy fingerprint images, where the OF estimation reliability of the algorithm is 6.46% and 32.93% higher than the gradient-based method and the PSD-based method, respectively.

Intra and inter-individual variability in functional connectomes of patients with First Episode of Psychosis

Patients with Schizophrenia may show different clinical presentations, not only regarding inter-individual comparisons but also in one specific subject over time. In fMRI studies, functional connectomes have been shown to carry valuable individual level information, which can be associated with cognitive and behavioral variables. Moreover, functional connectomes have been used to identify subjects within a group, as if they were fingerprints. For the particular case of Schizophrenia, it has been shown that there is reduced connectome stability as well as higher inter-individual variability. Here, we studied inter and intra-individual heterogeneity by exploring functional connectomes' variability and related it with clinical variables (PANSS Total scores and antipsychotic's doses). Our sample consisted of 30 patients with First Episode of Psychosis and 32 Healthy Controls, with a test-retest approach of two resting-state fMRI scanning sessions. In our patients' group, we found increased deviation from healthy functional connectomes and increased intragroup inter-subject variability, which was positively correlated to symptoms' levels in six subnetworks (visual, somatomotor, dorsal attention, ventral attention, frontoparietal and DMN). Moreover, changes in symptom severity were positively related to changes in deviation from healthy functional connectomes. Regarding intra-subject variability, we were unable to replicate previous findings of reduced connectome stability (i.e., increased intra-subject variability), but we found a trend suggesting that result. Our findings highlight the relevance of variability characterization in Schizophrenia, and they can be related to evidence of Schizophrenia patients having a noisy functional connectome.

Spectrum-effect relationship between UPLC fingerprints and melanogenic effect of Ruta graveolens L

A total of 29 batches of R. graveolens were used in this study, their fingerprints were obtained by ultra-performance liquid chromatography (UPLC) and their melanogenesis activities were evaluated. The common peaks were identified by quadrupole-orbitrap high-resolution mass spectrometry (Q-Orbitrap-HRMS). Eleven coumarins, six alkaloids, three flavonoids, three phenolic acids, and four other compounds were found. The spectrum-effect relationships between R. graveolens' chemical fingerprints, the melanin synthesis, and tyrosine's activation activities were established through chemometrics methods which in detail principal component analysis (PCA), gray correlation analysis (GRA), bivariate correlation analysis (BCA) and orthogonal partial least squares analysis (OPLS). The results showed that P18 (bergapten), P22 (isoimperatorin), P15 (kokusaginine), P7 (rutin), P12 (psoralen), and P13 (graveolinine) were relevant to intracellular melanin synthesis activity and tyrosinase activity. Among them, P18 (bergapten), P15 (kokusaginine), and P12 (psoralen) were validated with good melanogenesis activities. This study provides a research basis for future quality control and medicinal application of R. graveolens.

The developmental basis of fingerprint pattern formation and variation

Fingerprints are complex and individually unique patterns in the skin. Established prenatally, the molecular and cellular mechanisms that guide fingerprint ridge formation and their intricate arrangements are unknown. Here we show that fingerprint ridges are epithelial structures that undergo a truncated hair follicle developmental program and fail to recruit a mesenchymal condensate. Their spatial pattern is established by a Turing reaction-diffusion system, based on signaling between EDAR, WNT, and antagonistic BMP pathways. These signals resolve epithelial growth into bands of focalized proliferation under a precociously differentiated suprabasal layer. Ridge formation occurs as a set of waves spreading from variable initiation sites defined by the local signaling environments and anatomical intricacies of the digit, with the propagation and meeting of these waves determining the type of pattern that forms. Relying on a dynamic patterning system triggered at spatially distinct sites generates the characteristic types and unending variation of human fingerprint patterns.

Rapid identification, quantitation, and antioxidant activity evaluation of the components in Guanxin Shutong capsule with liquid chromatography and mass spectrometry

Guanxin Shutong capsule (GSC) is a traditional Chinese medicinal prescription used in the treatment of coronary heart disease (CHD) and angina pectoris in clinic. However, the chemical profile of GSC is still uncovered, which hindered the progress of pharmacological study and clinical application. Herein, high performance liquid chromatography (HPLC) together with high resolution mass spectrometry (HR-MS) techniques were employed to analyze the quality consistency and to identify chemical components in GSC. As a result, a total of 111 compounds were tentatively annotated. Quantitative analysis based on HPLC-ultraviolet detection (UV) was performed for 6 main components and fingerprints of 10 different batches of GSC were established. The developed method was validated for linearity, precision, repeatability, stability, and recovery. The quality evaluation and similarity analysis of the 10 batches were also performed. Furthermore, in vitro antioxidant activity assays demonstrated that GSC exhibited potential DPPH and hydroxyl radical scavenging capacities. Especially, salvianolic acids showed the strongest free radical scavenging capacities, which might be the main component for quality control of GSC.

UPLC-Q-TOF-MS and UPLC-QQQ-MS were used for the qualitative and quantitative analysis of oligosaccharides in Fufang Ejiao Syrup

Fufang Ejiao Syrup (FES) is a syrup made from Colla Corii Asini (CCA) and four botanicals (Codonopsis Radix (CR), Ginseng Radix et Rhizoma Rubra (GRRR), Rehmanniae Radix Praeparata (RRP) and Crataegi Fructus (CF)) as a result of modern processing and refining technology. FES has a lengthy history and is frequently used in clinical practice. Modern pharmacological studies have confirmed that oligosaccharides in any of the main medicinal herbs of FES, such as CR, GRRR, and RRP, have significant immune-enhancing effects. Therefore, the oligosaccharide component in FES could be its important pharmacologic substance, however, no studies on the content, structural analysis and source attribution of oligosaccharides in FES have been reported. The objective of this study is to systematically analyze the oligosaccharide in FES, compare the differences of the major oligosaccharides in different batches of FES produced by one manufacturer, and construct the content determination method for determining the content of the major oligosaccharides in FES, to provide technical support for FES quality assessment. This analysis revealed that a total of 13 oligosaccharides were identified from the FES, including 3 disaccharides, 4 trisaccharides, 3 tetrasaccharides, and 3 pentasaccharides. The constructed UPLC-QQQ-MS fingerprint of FES oligosaccharide is simple, stable, and reproducible, making it a useful tool for assessing FES's quality. There was a significant difference between the oligosaccharide fingerprints of 16 batches of FES,the results of fingerprint analysis combined with the statistical analysis suggested that the differences in stachyose, sucrose and raffinose contents in FES may be the reason for the great variations in oligosaccharide fingerprints of different batches of FES. For the 5 oligosaccharides in FES, the UPLC-QQQ-MS technique showed significant linearity in the linear range, along with good stability, repeatability, and recovery. Mannotriose was found to be higher in FES, followed by sucrose and stachyose, while kestose and raffinose were relatively lower. The results of this study reveal that oligosaccharides are important components of FES, and the method of fingerprinting and content determination constructed has strong practical value and is expected to be used for FES quality control.

Fingerprint image enhancement using multiple filters

Biometrics is the measurement of an individual's distinctive physical and behavioral characteristics. In comparison to traditional token-based or knowledge-based forms of identification, biometrics such as fingerprints, are more reliable. Fingerprint images recorded digitally can be affected by scanner noise, incorrect finger pressure, condition of the finger's skin (wet, dry, or abraded), or physical material it is scanned from. Image enhancement algorithms applied to fingerprint images remove noise elements while retaining relevant structures (ridges, valleys) and help in the detection of fingerprint features (minutiae). Amongst the most common image enhancement filters is the Gabor filter, however, given their restricted maximum bandwidth as well as limited range of spectral information, it falls short. We put forward a novel method of fingerprint image enhancement using a combination of a diffusion-coherence filter and a 2D log-Gabor filter. The log-Gabor overcomes the limitations of the Gabor filter while Coherence Diffusion mitigates noise elements within fingerprint images. Implementation is done on the FVC image database and assessed via visual comparison with coherence diffusion used disjointedly and with the Gabor filter.

The confound of head position in within-session connectome fingerprinting in infants

Individuals differ in their functional connectome, which can be demonstrated using a "fingerprinting" analysis in which the connectome from an individual in one dataset is used to identify the same person from an independent dataset. Recently, the origin of these fingerprints has been studied by examining if they are present in infants. The results have varied considerably, with identification rates from 10 to 90%. When fingerprinting has been performed by splitting a single imaging session into two split-sessions (within session), identification rates were higher than when two full-sessions (between sessions) were compared. This study examined whether a methodological difference could account for this variation. It was hypothesized that the infant's exact head position in the head coil may affect the measured connectome, due to the gradual inhomogeneity of signal-to-noise in phased-array coils and the breadth of possible positions for a small infant head in a head coil. This study examined the impact of this using resting state functional MRI data from the Developing Human Connectome Project second release. Using functional timeseries, fingerprinting identification was high (84-91%) within a session while between sessions it was low (7%).Using N = 416 infants' head positions, a map of the average signal-to-noise across the physical volume of the head coil was calculated and was used (independent group of 44 infants with two scan sessions) to demonstrate a significant relationship between head position in the head coil and functional connectivity. Using only the head positions (signal-to-noise values extrapolated from the group average map) of the independent group of 44 infants, high identification success was achieved across split-sessions (within session) but not full-sessions (between sessions). Using a model examining factors influencing the stability of the functional connectome, head position was seen as the strongest of the explanatory variables. We conclude within-session fingerprinting is affected by head position and future infant functional fingerprint analyses must use a different strategy or account for this impact.

Qualitative determination of volatile substances in different flavored cigarette paper by using headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) combined with chemometrics

In order to investigate the difference of volatile substances among flavored cigarette paper, which are supplied by several manufacturers with different batches, the stability of the complex system of scented cigarette paper was analyzed and evaluated. In this study, Headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) was used to detect the aroma compounds of 23 flavored cigarette paper samples. Based on fingerprint analysis, the differences and changes of aroma compounds of different samples were studied in the form of data visualization. Principal component analysis, partial least squares regression analysis, cluster heatmap analysis and artificial neural network analysis were used to evaluate the stability of different cigarette paper. The results show that: A total of 29 volatile substances were identified from different scented cigarette paper. Fingerprint analysis revealed that the volatile substances of different cigarette paper samples were roughly the same, but not the content. The results of chemometrics analysis showed that there were significant differences in the characteristic aroma compounds of cigarette paper from different manufacturers. HS-GC-IMS technology combined with chemometrics method could be applied to determine the difference of volatile substances among different flavored cigarette paper, which theoretically and technically supported the quality stability maintenance and identification of flavored cigarette paper processed in different places.

Chemical profiling and quality evaluation of Callicarpa nudiflora from different regions in China by UPLC-QTOF-MS fingerprint

Callicarpa nudiflora, belonging to the family Verbenaceaae, is wildly used as a traditional Chinese herbal medicine (Luo-hua-zi-zhu) for hemostasis, antibiosis and antiphlogosis in clinlic. However, the underlying chemical basis of C. nudiflora for the significant effects remains obscure. Hence, an ultra-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry method was established for the characterization of multi-constituents in C. nudiflora. As a result, 57 chemical compounds were identified based on their retention times, accurate masses and MS/MS data, and 20 of them were uncovered for the first time in C. nudiflora. In addition, an optimized UHPLC fingerprint analysis, combined with chemometrics including similarity analysis , principal component analysis and partial least squares-discriminant analysis was developed for quality assessment and origin discrimination of C. nudiflora. Multivariate data analysis revealed the resemblances and differences of C. nudiflora related to regions, while partial least squares-discriminant analysis screened nine characteristic markers including luteoloside, acteoside, luteolin-4'-O-β-D-glucopyranoside, pachypodol, isoquercitrin, nudifloside, 5,7,3',4'-tetrahydroxy-8-methoxy-6-C-β-D-glucopyranosyl flavone, 7α-acetoxysandaracopimaric acid and sandaracopimaric acid which contributed the most to the classification. This was the first report on the comprehensive profiling of chemical components in C. nudiflora, which helped to uncover the material basis of C. nudiflora and possess potential value for quality evaluation and clinical application purpose.

Identification of specific halogenated polycyclic aromatic hydrocarbons in surface soils of petrochemical, flame retardant, and electronic waste dismantling industrial parks

Halogenated polycyclic aromatic hydrocarbons (Cl/Br-PAHs) have received tremendous attention due to their high toxicity. To identify the emission pattern of Cl/Br-PAHs from various industrial productions, understand the formation mechanisms and the influence on the surroundings, this study investigated the surface soils of three typical industrial parks. Generally, traces of Cl-PAHs were much lower than Br-PAHs. The mean Cl-PAH concentrations followed the trend of petrochemical industrial park (3.12 ng/g), brominated flame retardant (BFR) manufacturing park (1.48 ng/g), and electronic waste dismantling park (0.26 ng/g). However, the BFR manufacturing park had the highest mean Br-PAH concentration (21.6 ng/g), significantly higher than the other two parks. Generally, higher levels of the chemicals were found in the parks than in their surroundings, except for the electronic waste dismantling park. The massive addition of chlorine additives in crude oil and its by-products, plus the enormous quantity of brominated brines used in BFR productions, favor Cl/Br-PAH formation. Analyzing the homolog compositions of Cl/Br-PAHs suggested that 3- or 4-ring Cl/Br-PAHs were typically come from the petrochemical industrial park and electronic waste dismantling park. Contrarily, 4- or 5-ring Cl/Br-PAHs were predominantly come from the BFR manufacturing activity. This study provides fingerprints to trace the Cl/Br-PAH emissions during industrial production and analyzes the formation mechanism.

Metabolomic profiling for drug-induced liver injury with autoantibodies

BACKGROUNDS

Drug induced liver injury (DILI) is sometimes similar to autoimmune hepatitis (AIH) in serology and histology. Clinicians empirically screened DILI with significant autoimmune characteristics to implement clinical intervention. We tried to characterize DILI with autoantibodies by metabolomics.

METHODS

Untargeted metabolomics coupled with pattern recognition approaches were performed on sera samples including AIH (n = 59), DILI with autoantibodies (DILI^Ab+, n = 68), and DILI without autoantibodies (DILI^Ab-, n = 75). The differential metabolites and fingerprint metabolites between AIH and DILI^Ab- were screened by orthogonal partial least squares-discriminant analysis and hierarchical clustering respectively.

RESULTS

Of the 388 annotated differential metabolites between AIH and DILI^Ab-, 74 fingerprint metabolites were screened. The eigenmetabolite compressed from the fingerprint possessed high discrimination efficacy (AUC:0.891; 95 %CI, 0.838-0.944). In the fingerprint-based PCA model, AIH and DILI^Ab- were separated into three regions: the "pure region" of AIH (Region 1), the "pure region" of DILI^Ab- (Region 3), the mixture region of AIH and DILI^Ab- (Region 2). After incorporated into the PCA model, DILI^Ab+ samples were distributed into the three regions, indicating that DILI^Ab+ samples had different etiological tendencies. Moreover, the fingerprint-based radar model verified the results of PCA model characterizing DILI^Ab+. Notably, the antibody titers of DILI^Ab+ in the three regions did not differ significantly, while the response rates for glucocorticoids were obviously different. The metabolic difference among DILI^Ab+ in different regions mainly lies in energy metabolism.

CONCLUSIONS

In terms of metabolic signature, DILI^Ab+ may not be a community of same pathogenesis, including AIH-inclined parts. Which deserves further study.

Detection of pesticides in food products using paper-based devices by UV-induced fluorescence spectroscopy combined with molecularly imprinted polymers

In this proof-of-concept study, we explore the detection of pesticides in food using a combined power of sensitive UV-induced fingerprint spectroscopy with selective capture by molecularly imprinted polymers (MIPs) and portable cost-effective paper-based analytical devices (PADs). The specific pesticides used herein as model compounds (both pure substances and their application products for spraying), were: strobilurins (i.e. trifloxystrobin), urea pesticides (rimsulfuron), pyrethroids (cypermethrine) and aryloxyphenoxyproponic acid herbicides (Haloxyfop-methyl). Commercially available spraying formulations containing the selected pesticides were positively identified by MIP-PADs swabs of sprayed apple and tomato. The key properties of MIP layer - imprinting factor (IF) and selectivity factor (α) were characterized using trifloxystrobin (IF-3.5, α-4.4) was demonstrated as a potential option for in-field application. The presented method may provide effective help with in-field testing of food and reveal problems such as false product labelling.

A strategy for quality control of ginkgo biloba preparations based on UPLC fingerprint analysis and multi-component separation combined with quantitative analysis

Background

Many studies have assessed the fingerprint and quantitative analysis of Ginkgo biloba preparations, but the fingerprint mainly focuses on flavonoid glycosides. However, according to our previous study, the differences among diverse manufacturers mainly involve organic acids.

Methods

A novel reverse-phase liquid chromatography assay using diode array detection was developed for evaluating Ginkgo biloba preparations for quality based on a chromatographic fingerprint allowing the simultaneous assessment of eleven compounds, including four organic acids, six flavonol glycosides and one flavonoid aglycone. And the method was applied to 51 batches of Ginkgo biloba preparations from manufacturers in China. Chemometric approaches were performed for evaluating 51 batches of Ginkgo biloba preparations from various manufacturers.

Results

The similarity values among the chromatograms of 51 samples ranged from 0.45 to 1.00, showing that the quality of Ginkgo biloba preparations produced by different manufacturers varied greatly. Data analysis of the 51 batches of GBP samples suggested significant variations of the total contents of all 11 targets, also demonstrating the quality difference of GBP samples. There were significant differences in organic acids in particular.

Conclusion

Combining the chemical fingerprint and quantitative assessment revealed significant variations in the examined commercial products with regard to organic acids. Thus, this study provided a more comprehensive tool for monitoring the quality consistency of Ginkgo biloba preparations.

Chemical fingerprinting and characterization of spilled oils and burnt soot particles - A case study on the Sanchi oil tanker collision in the East China Sea

The condensate spill accident from the Sanchi oil tanker collision in the East China Sea is unique in world history. To date, the spilled and burnt amounts of condensate remain unknown. The present study demonstrates the chemical fingerprints of a surrogate condensate (SC) from the same source, and of the carried heavy fuel oil (HFO) of the Sanchi accident. The evaporative features of the condensate are demonstrated by allowing the SC to naturally volatilize in a dark fume hood. In addition, the combustion emission of the SC is characterized by conducting a laboratory-scale combustion experiment. The evaporation experiment suggests that the volatilization process plays a significant role in the weathering of the condensate. The results show that the SC and HFO can be clearly distinguished based on their chemical fingerprints of C₂₇-C₃₅ hopanes and C₉-C₃₆ n-alkanes, along with priority polycyclic aromatic hydrocarbons (PAHs) and their alkylated derivatives. The compositional data reveal that the lighter component is predominant in the SC, thereby supporting its high volatility and flammability. The greater amounts of heavier components in the HFO indicate its long-term degradation and potential ecological risks to the environment. Further, the trisnorhopane thermal indicator (T_s/T_m) and C₂₉/C₃₀ ratio of hopanes are validated for identification of the SC and the HFO. More importantly, the changes in the hopane ratios of the soot particles are analyzed for the first time in this study, and the results demonstrate the validity of using hopane ratios to fingerprint the condensate soot particles. The diagnostic ratios of 2-MP/1-MP, 9/4-MP/1-MP, and InP/(InP+BghiP) also show decent performance on source identification after the condensate evaporation and combustion processes.

Geographical authentication of virgin olive oil by GC-MS sesquiterpene hydrocarbon fingerprint: Verifying EU and single country label-declaration

According to the last report from the European Union (EU) Food Fraud Network, olive oil tops the list of the most notified products. Current EU regulation states geographical origin as mandatory for virgin olive oils, even though an official analytical method is still lacking. Verifying the compliance of label-declared EU oils should be addressed with the highest priority level. Hence, the present work tackles this issue by developing a classification model (PLS-DA) based on the sesquiterpene hydrocarbon fingerprint of 400 samples obtained by HS-SPME-GC-MS to discriminate between EU and non-EU olive oils, obtaining an 89.6% of correct classification for the external validation (three iterations), with a sensitivity of 0.81 and a specificity of 0.95. Subsequently, multi-class discrimination models for EU and non-EU countries were developed and externally validated (with three different validation sets) with successful results (average of 92.2% of correct classification for EU and 96.0% for non-EU countries).

Towards the protection of ammunition headstamps during fingermark enhancement processing; a preliminary study

Forensic recovery from fired ammunition casings remains one of the most challenging tasks during high-profile investigations. Often, the decision must be made between screening for DNA or fingerprints, and, in doing so, the impact these processes will have on the examination of ballistic markings imparted on the ammunition from the firearm itself. Traditionally, fingermark enhancement processes have yielded low success rates in their efforts to identify suspects by enhancing friction ridge detail left on the cartridge casings. Moreover, the enhancement methods utilised may often induce detrimental physical changes to the casing(s), rendering them unsuitable for subsequent ballistics (marking) examination. Recently, new technology has been shown to increase the success rate of fingermark recovery from fired ammunition, and the growing adoption of such innovation means that new challenges are encountered to maximise evidence recovery and streamline forensic workflows. One such example arises from the potential obscuration of the ammunition headstamp area during such treatments. Accordingly, this study outlines the preliminary investigations and developments of a polymer mask substrate that serves to protect the headstamp of fired ammunition casings during relevant fingermark enhancement processes. The technique also has the capacity to be used as a surface protection device to eliminate unwanted chemical deposition across other areas of interest and evidence types.

Geographical origin of guarana seeds from untargeted UHPLC-MS and chemometrics analysis

Guarana is one of the most popular functional foods in the Amazon and widely used in the world. This work aimed to study the chemical composition of guarana produced by the main producing states and try to associate their geographical origin. We report an untargeted metabolomic analytical method performed by UHPLC-ESI-IT-MS and multivariate analysis (chemometrics) of guarana seeds, which was able to separate the samples according to their geographical origin. Previously, full chromatogram range was analyzed, and it could be observed that the two main compounds, catechin and epicatechin, have introduced large data variance in PCA analysis not related to the geographical origin of samples. After exclusion of the corresponding peaks, it was possible to obtain three main clusters corresponding to samples from Amazonas, Bahia and Mato Grosso. Thirteen dimers and trimers of procyanidins type A and B were identified by PCA and UHPLC-ESI-Q-TOF-MS/MS, as chemical markers of geographic origin.

Detecting phishing webpages via homology analysis of webpage structure

Phishing webpages are often generated by phishing kits or evolved from existing kits. Therefore, the homology analysis of phishing webpages can help curb the proliferation of phishing webpages from the source. Based on the observation that phishing webpages belonging to the same family have similar page structures, a homology detection method based on webpage clustering according to structural similarity is proposed. The method consists of two stages. The first stage realizes model construction. Firstly, it extracts the structural features and style attributes of webpages through the document structure and vectorizes them, and then assigns different weights to different features, and measures the similarity of webpages and guides webpage clustering by webpage difference index. The second phase completes the detection of webpages to be tested. The fingerprint generation algorithm using double compressions generates fingerprints for the centres of the clusters and the webpages to be tested respectively and accelerates the detection process of the webpages to be tested through bitwise comparison. Experiments show that, compared with the existing methods, the proposed method can accurately locate the family of phishing webpages and can detect phishing webpages efficiently.

Towards a high-precision contactless fingerprint scanner for biometric authentication

The raging COVID-19 pandemic accentuates the urgent and compelling need for non-contact fingerprinting biometric authentication devices to mitigate the transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other contagious infections. Current approaches to contactless fingerprinting scanners suffer limitations ranging from poor compatibility with two-dimensional equivalent touch-based fingerprint images to perspective distortions, inconstant resolution, motion blur images and low correlation factors. Herein, these constraints are tackled by implementing a system that enables the positioning of the target finger(s) at fixed vertical and horizontal distances away from the camera lens without the physical contact of the fingers with the device framework during scanning. A high-precision fingerprint pattern recognition of up to 97.51% correlation factor has been achieved, using this contactless method, by varying the background illuminating light and implementing two-dimensional imaging techniques and near-constant resolution. Additionally, a convenient contactless fingerprint acquisition process is reinforced through a unique architectural design.

European fingerprint study on omeprazole drug substances using a multi analytical approach and chemometrics as a tool for the discrimination of manufacturing sources

Like drug products, Active Pharmaceutical Ingredients (APIs) are subject to substandard and falsification issues, which represent a threat to patient health. In order to monitor the quality of drug substances and prevent the use of non-compliant APIs, Official Medicine Control Laboratories work together in a European network developing coordinated strategies and programmes. The API working group proposed a market surveillance study on omeprazole and omeprazole magnesium with the objectives of controlling the pharmaceutical quality of samples, checking compliance with the monographs of the European Pharmacopoeia, and collecting analytical fingerprints that could be further used to differentiate manufacturing sources for future authenticity investigations. The study described in this article reports the analysis carried out by 7 European laboratories on 28 samples from 11 manufacturers with 5 analytical techniques (related substances with HPLC, residual solvents with GC-MS, near infrared spectroscopy, proton nuclear magnetic resonance spectroscopy and X-ray powder diffractometry). The large amount of resulting analytical data were centralized and treated with two chemometric methods: Principal Component Analysis and Hierarchical Clustering Analysis. Data were analyzed separately and in combination (data fusion), allowing us to conclude that NMR and XRPD were suitable to differentiate samples originating from 9 out of 11 manufacturers. Analytical fingerprints associated with chemometrics were demonstrated to be a valuable methodology to discriminate manufacturers of omeprazole and omeprazole magnesium APIs and detect future substandard and falsified APIs.

Study on the Chemical Changes of the Traditional Process from Polygonatum kingianum by Multiple Fingerprint Profiles Combined with Multivariate Methods

Polygonati Rhizoma (Huangjing) is traditional medicine in China, which can only be used as medicine after being processed. However, there is a limited theoretical basis for analyzing the change of chemical components in traditional processing. In the present study, the analytical techniques including Fourier transform infrared spectroscopy, high-performance gel permeation chromatography-evaporative light scattering detector, and high-performance liquid chromatography-diode array detector were proposed to perform multiple fingerprint analyses of the changes of the processed materials; the total sugar was also determined. Moreover, the chemometric studies, including hierarchical cluster analysis and principal component analysis, were used to visualize the discrimination of raw and processed materials. The results revealed that the chemical constituents had been profoundly changed after the process. In conclusion, these methods could be successfully used to compare raw and processed materials of P. kingianum, which could be used to elaborate the rationality of processing from the perspective of chemical composition.

Chemical profiling and quality evaluation of Pogostemon cablin Benth by liquid chromatography tandem mass spectrometry combined with multivariate statistical analysis

Pogostemon cablin Benth (PCB) is a well-known traditional Chinese medicine that has been used for treatment of many ailments for several centuries. In presently, the chemical profiling and quality control study of PCB has mainly concentrated on the volatile fractions. However, the non-volatile chemical profile of PCB was still unclear. In this study, 73 non-volatile constituents (i.e., 33 flavonoids, 21 organic acids, 9 phenylpropanoids, 4 sesquiterpenes, 3 alkaloids, and 3 other types of compounds) were identified and characterized in PCB using high performance liquid chromatography coupled with quadruple time-of-flight tandem mass spectrometry (HPLC-Q-TOF-MS). Meanwhile, to assess PCB samples, an established HPLC-Q-TOF-MS fingerprint was combined with multivariate statistical analysis that included similarity analysis (SA), hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA). The PCB samples could be classified into two groups (herbal decoction pieces and processed medicinal materials), and acteoside, isoacteoside, 4',6-Dihydroxy-5,7-dimethoxyflavone, pachypodol and pogostone were screened as the potential chemical markers that attributed classification. In addition, nine representative components (pachypodol, vicenin-2, apigenin, rhamnocitrin, acteoside, isoacteoside, chlorogenic acid, azelaic acid and pogostone) in PCB were simultaneously determined by using an ultra-high-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UPLC-QQQ-MS/MS). This study is the first to describe the chemical profile of PCB using liquid chromatography tandem mass spectrometry, which would improve our understanding of the substance basis of PCB and is helpful to the PCB further quality evaluation.

GEONs API fingerprint project: Selection of analytical techniques for clustering of sildenafil citrate API samples

Through its Active Pharmaceutical Ingredient Working Group (API-WG) the General European Official Medicines Control Laboratory (OMCL) Network (GEON), co-ordinated by the European Directorate for the Quality of Medicines & HealthCare (EDQM), regularly organises market surveillance studies for specific APIs for conformity to their monograph in the European Pharmacopoeia. During the past years some studies were combined with a fingerprint study of the APIs. The idea is to obtain a fingerprint for each manufacturer of the API under investigation, allowing the OMCL network to identify future samples as well as to detect substandard and falsified APIs. This paper reports the results of the latest fingerprint study, organised on sildenafil citrate API samples. Seventy-nine samples from 14 different manufacturers were collected throughout the Network. Fingerprint data was collected through Mid-Infrared spectroscopy, Raman spectroscopy, liquid chromatography for related substances, gas chromatography for residual solvents, X-ray diffraction and Nuclear Magnetic Resonance (NMR) spectroscopy. Chemometrics applied to the collected data showed that all manufacturers could be discriminated based on the data of only three of these tests, i.e. gas chromatography for residual solvents, X-ray diffraction and proton NMR. Suspicious API samples for sildenafil citrate will therefore be analysed in the future with the selected techniques in order to link the sample to a manufacturer or demonstrate the absence of such link. If the sample cannot be attributed to one of the manufacturers, further analysis and research on provenance and identity will be required. Of course, if the suspected sample claims to originate from one of the manufacturers included in the study, analysis can be limited to the test distinguishing this manufacturer.

Rhodanine-based fluorometric sequential monitoring of silver (I) and iodide ions: Experiment, DFT calculation and multifarious applications

A simple rhodanine derived fluorophoric unit has been designed for selective detection of Ag⁺ and I^- ions in DMSO-H₂O medium. The sensor R1 showed an obvious "turn-on" fluorescence response toward Ag⁺ due to the inhibition of both C-N single bond free rotation, internal charge transfer (ICT) and the formation of chelation enhanced fluorescence (CHEF) effects. The fluorescence quantum yield (Φ) was increased from 0.0013 to 0.032 for receptor R1 upon the Ag⁺-complexation. In addition, the 1:1 complexing stoichiometry was employed based on Job's plot analysis with detection limit of 24.23 × 10^-7 M. Conversely, receptor R1+Ag⁺ particularly detects I^- ion over other co-existing anions by the "turn-off" fluorescence response due to the formation of AgI, displacing the receptor R1 with the quantum yield of 0.0014. The detection limit was calculated to be 22.83 × 10^-7 M. The sensing behaviour of receptor R1 toward Ag⁺ was also supported by density functional theory (DFT) calculations. Moreover, the sensing ability of reported receptor R1 could be exercised in multifarious applications like paper strip, silica-supported analysis, staining test for latent finger print, logical behaviour, smartphone-assisted quantitative detection and real water samples studies.