Cinnabar(HgS) was widely used in ancient times for medicinal purposes, religious rituals, and pigments. A group of bright red powdery clumps was excavated from Mawangdui Tomb No.3 of the Han Dynasty. Early studies considered the clumps as evidence of cinnabar's medicinal use during the Qin-Han period. This study employed a range of archaeometric techniques, including extended-depth-of-field stereo imaging, micro-CT, scanning electron microscopy-energy dispersive spectroscopy, Raman spectroscopy, and Fourier transform infrared spectrometry FTIR, to systematically analyze the material composition and structural characteristics of these remains. The results revealed that the cinnabar particles were granular, finely ground, and tightly bound to silk matrix, with no detectable excipients typically associated with medicinal formulations. Micro-CT imaging indicated a well-preserved textile structure, with clear signs of sedimentary accumulation and mechanical damage. Based on historical and archaeological studies, this study suggested that these remains were more likely degraded accumulations of cinnabar-colored silk textiles rather than medicinal cinnabar. By clarifying the diversity of ancient cinnabar applications and preservation states, this study provides new insights for the archaeological identification of mineral medicinal materials and contributes to the standardized study of Chinese medicinal materials and understanding of the historical use of cinnabar.
History, Ancient ; China ; Humans ; Medicine, Chinese Traditional/history* ; Archaeology ; Drugs, Chinese Herbal/history* ; Spectroscopy, Fourier Transform Infrared ; Spectrum Analysis, Raman ; Mercury Compounds

OBJECTIVES: To evaluate the causal association between circulating levels of zinc, magnesium, and other minerals and autism spectrum disorder (ASD). METHODS: A two-sample Mendelian randomization (MR) analysis was performed using summary statistics from large-scale genome-wide association studies of European populations, including 18 382 ASD cases and 27 969 controls. Genetic data for iron, calcium, and magnesium were obtained from the UK Biobank, and data for zinc and selenium were sourced from an Australian-British cohort. A total of 351 genetic instrumental variables were selected. Causal inference was performed using inverse-variance weighting as the primary analysis method. Sensitivity analyses were performed by Cochran's Q test and MR-PRESSO global test to assess the robustness of the findings. RESULTS: No statistically significant causal effect was observed for circulating zinc, magnesium, calcium, selenium, or iron levels on ASD risk (all P>0.05). The odds ratios and 95% confidence intervals from the inverse-variance weighting analysis were 0.934 (0.869-1.003) for zinc, 1.315 (0.971-1.850) for magnesium, 1.055 (0.960-1.159) for calcium, 1.015 (0.953-1.080) for selenium, and 0.946 (0.687-1.303) for iron. Sensitivity analysis revealed significant heterogeneity in the causal association between circulating calcium and ASD (P=0.006), while the effect estimate remained stable after MR-PRESSO correction (P=0.487). The causal effect estimates for the remaining minerals demonstrated good robustness. CONCLUSIONS This study did not find significant evidence supporting a causal association between circulating zinc, magnesium, calcium, selenium, or iron levels and ASD risk, providing important clues for the etiology of ASD and precision nutritional interventions.
Humans ; Mendelian Randomization Analysis ; Autism Spectrum Disorder/genetics* ; Magnesium/blood* ; Zinc/blood* ; Minerals/blood* ; Genome-Wide Association Study ; Selenium/blood*

The presence of a positive deep surgical margin in tongue squamous cell carcinoma (TSCC) significantly elevates the risk of local recurrence. Therefore, a prompt and precise intraoperative assessment of margin status is imperative to ensure thorough tumor resection. In this study, we integrate Raman imaging technology with an artificial intelligence (AI) generative model, proposing an innovative approach for intraoperative margin status diagnosis. This method utilizes Raman imaging to swiftly and non-invasively capture tissue Raman images, which are then transformed into hematoxylin-eosin (H&E)-stained histopathological images using an AI generative model for histopathological diagnosis. The generated H&E-stained images clearly illustrate the tissue's pathological conditions. Independently reviewed by three pathologists, the overall diagnostic accuracy for distinguishing between tumor tissue and normal muscle tissue reaches 86.7%. Notably, it outperforms current clinical practices, especially in TSCC with positive lymph node metastasis or moderately differentiated grades. This advancement highlights the potential of AI-enhanced Raman imaging to significantly improve intraoperative assessments and surgical margin evaluations, promising a versatile diagnostic tool beyond TSCC.
Humans ; Spectrum Analysis, Raman/methods* ; Tongue Neoplasms/diagnostic imaging* ; Carcinoma, Squamous Cell/diagnostic imaging* ; Artificial Intelligence ; Margins of Excision

Gongju(Chrysanthemum morifolium) is one of the five major medicinal Chrysanthemum varieties included in the Chinese Pharmacopoeia. In recent years, its cultivation areas have changed significantly, resulting in mixed quality of the medicinal herbs. In this study, Gongju cultivated in Anhui, Yunnan, Chongqing, and other places were selected as research objects. Hyperspectral data were collected in the visible-near-infrared(VNIR) and short-wave infrared(SWIR) bands using different modes, such as corolla facing up(A) and flower base facing up(B). After pre-processing the hyperspectral data using five methods, including multiplicative scatter correction(MSC), Savitzky-Golay smoothing(SG), first derivative(D1), second derivative(D2), and standard normal variate(SNV), partial least squares discriminant analysis(PLSDA), random forest(RF), and support vector machine(SVM) were used to establish origin identification models of Gongju at the two geographical scales of the province and the city-county in Anhui province. The accuracy of the prediction results was used as an evaluation index to select the optimal models, and the classification performance of the models was evaluated by confusion matrix. The results showed that the flower base facing up(B) collection model combined with second derivative pretreatment and RF method was the best model for both geographical scale identification models. The modeling effect of the full-band(VNIR + SWIR) was slightly better than that of the single band, with the accuracy of the prediction set in the province and city-county regions reaching 99.69% and 99.40%, respectively. The competitive adaptive reweighted sampling algorithm(CARS), successive projections algorithm(SPA), and variable iterative space shrinkage approach(VISSA) were further used to screen the feature wavelength modeling. The number of feature wavelengths screened by CARS was fewer, and the prediction set accuracy of the two geographical scales models after optimization could reach 99.56% and 98.65%, which was basically comparable to the full-band model. However, the removal of redundant variables could greatly reduce the complexity of the model. The hyperspectral technology combined with the chemometrics model established in this study can achieve the origin identification of Gongju at different geographical scales, providing a theoretical basis and technical reference for the construction of a rapid detection system for Gongju origin and the development of exclusive miniaturized instrumentation and equipment systems.
Chrysanthemum/growth & development* ; China ; Support Vector Machine ; Geography ; Discriminant Analysis ; Spectroscopy, Near-Infrared/methods* ; Spectrum Analysis/methods* ; Drugs, Chinese Herbal/analysis* ; Least-Squares Analysis

Objective: To establish a inductively coupled plasma mass spectrometry method for the determination of trace cobalt and tungsten in human urine. Methods: The authors used 1% nitric acid solution as diluent in October-December 2021, the sample dilution factor and internal standard element were optimized by single factor rotation experiment, and the difference between the working curve and the standard curve was compared. Results: The method uses working curve to determine cobalt and tungsten in urine, the linear range of this method was 0.0~10.0 μg/L, the correlation coefficient was 0.999 9, the detection limits respectively were 0.005 μg/L (cobalt) and 0.09 μg/L (tungsten), the recoveries of samples respectively were 87.0%~100.2% (cobalt) and 89.4%~104.8% (tungsten), the relative standard deviations respectively were 0.4%~4.4% (cobalt) and 0.6%~3.8% (tungsten) . Conclusion: A simple and rapid method for determination of cobalt and tungsten in urine has been established. This method has the advantages of simple operation, high sensitivity, low detection limit and good stability. It is suitable for determination of cobalt and tungsten in urine of all kinds of people.
Humans ; Cobalt/analysis* ; Tungsten/analysis* ; Spectrum Analysis ; Nitric Acid ; Mass Spectrometry

Due to the high complexity and subject variability of motor imagery electroencephalogram, its decoding is limited by the inadequate accuracy of traditional recognition models. To resolve this problem, a recognition model for motor imagery electroencephalogram based on flicker noise spectrum (FNS) and weighted filter bank common spatial pattern ( wFBCSP) was proposed. First, the FNS method was used to analyze the motor imagery electroencephalogram. Using the second derivative moment as structure function, the ensued precursor time series were generated by using a sliding window strategy, so that hidden dynamic information of transition phase could be captured. Then, based on the characteristic of signal frequency band, the feature of the transition phase precursor time series and reaction phase series were extracted by wFBCSP, generating features representing relevant transition and reaction phase. To make the selected features adapt to subject variability and realize better generalization, algorithm of minimum redundancy maximum relevance was further used to select features. Finally, support vector machine as the classifier was used for the classification. In the motor imagery electroencephalogram recognition, the method proposed in this study yielded an average accuracy of 86.34%, which is higher than the comparison methods. Thus, our proposed method provides a new idea for decoding motor imagery electroencephalogram.
Brain-Computer Interfaces ; Imagination ; Signal Processing, Computer-Assisted ; Electroencephalography/methods* ; Algorithms ; Spectrum Analysis

Corydalis hendersonii(CH) is a Tibetan folk medicine with the functions of clearing heat, detoxifying, cooling blood, checking diarrhea, and lowering blood pressure. It is often used to treat high altitude polycythemia, vasculitis, peptic ulcer, and diarrhea. Nine compounds were separated from the ethanol extract of CH by silica gel, ODS, Sephadex LH-20 chromatography and semi-preparative HPLC. Their structures were identified as hendersine H(1),hendersine I(2), dehydrocheilanthifoline(3), protopine(4), izmirine(5), 6,7-methylenedioxy-1(2H)-isoquinolinone(6), icariside D_2(7), ethyl 4-(β-D-glucopyranosyloxy)-3-methoxybenzoate(8), 3-hydroxy-4-methoxybenzoic acid(9), respectively, by the spectroscopic data analysis and comparison with those in the literature. Among them, compounds 1 and 2 are new isoquinoline alkaloids, and compounds 7-9 are reported the first time for Corydalis. The hypoglycemic model of H9c2 cardiomyocytes and the inflammatory model of H9c2 cardiomyocytes induced by conditional supernatant were employed to determine the activities of the above compounds. The results showed that 20 μmol·L~(-1) compound 1 had a protective effect on H9c2 cardiomyocytes and 10 μmol·L~(-1) compounds 4 and 5 inhibited H9c2 cardiomyocyte inflammation induced by conditional supernatant.
Humans ; Corydalis/chemistry* ; Alkaloids/chemistry* ; Inflammation ; Spectrum Analysis ; Isoquinolines/pharmacology*

Urinary system tumors affect a huge number of individuals, and are frequently recurrent and progressing following surgery, necessitating lifelong surveillance. As a result, early and precise diagnosis of urinary system cancers is important for prevention and therapy. Histopathology is now the golden stan-dard for the diagnosis, but it is invasive, time-consuming, and inconvenient for initial diagnosis and re-gular follow-up assessment. Endoscopy can directly witness the tumor's structure, but intrusive detection is likely to cause harm to the patient's organs, and it is apt to create other hazards in frequently examined patients. Imaging is a valuable non-invasive and quick assessment tool; however, it can be difficult to define the type of lesions and has limited sensitivity for early tumor detection. The conventional approaches for detecting tumors have their own set of limitations. Thus, detection methods that combine non-invasive detection, label-free detection, high sensitivity and high specificity are urgently needed to aid clinical diagnosis. Optical diagnostics and imaging are increasingly being employed in healthcare settings in a variety of sectors. Raman scattering can assess changes in molecular signatures in cancer cells or tissues based on the interaction with vibrational modes of common molecular bonds. Due to the advantages of label-free, strong chemical selectivity, and high sensitivity, Raman scattering, especially coherent Raman scattering microscopy imaging with high spatial resolution, has been widely used in biomedical research. And quantity studies have shown that it has a good application in the detection and diagnosis of bladder can-cer, renal clear cell carcinoma, prostate cancer, and other cancers. In this paper, several nonlinear imaging techniques based on Raman scattering technology are briefly described, including Raman spectroscopy, coherent anti-Stokes Raman scattering, stimulated Raman scattering, and surface-enhanced Raman spectroscopy. And we will discuss the application of these techniques for detecting urologic malignancy. Future research directions are predicted using the advantages and limitations of the aforesaid methodologies in the research. For clinical practice, Raman scattering technology is intended to enable more accurate, rapid, and non-invasive in early diagnosis, intraoperative margins, and pathological grading basis for clinical practice.
Humans ; Male ; Microscopy/methods* ; Radiopharmaceuticals ; Spectrum Analysis, Raman/methods* ; Technology ; Urologic Neoplasms/diagnosis*

In order to evaluate the composition and distribution characteristics of inorganic elements in Laminaria japonica, this study employed inductively coupled plasma mass spectrometry(ICP-MS) to detect the inorganic elements and used high performance liquid chromatography tandem ICP-MS(HPLC-ICP-MS) to determine the content of different arsenic species in L. japonica from diffe-rent origins. Micro X-ray fluorescence(Micro-XRF) was used to determine micro-area distribution of inorganic elements in L. japonica. The results showed that the average content of Mn, Fe, Sr, and Al was high, and that of As and Cr exceeded the limits of the national food safety standard. According to the results of HPLC-ICP-MS, arsenobetaine(AsB) was the main species of As contained in L. japonica. The more toxic inorganic arsenic accounts for a small proportion, whereas its content was 1-4 times of the limit in the national food safety standard. The results of Micro-XRF showed that As, Pb, Fe, Cu, Mn, and Ni were mainly distributed on the surface of L. japonica. Among them, As and Pb had a clear tendency to diffuse from the surface to the inside. The results of the study can provide a basis for the processing as well as the medicinal and edible safety evaluation of L. japonica.
Arsenic/analysis* ; Chromatography, High Pressure Liquid/methods* ; Laminaria ; Mass Spectrometry/methods* ; Spectrum Analysis ; Trace Elements/analysis*

Hyperspectral imaging technology can obtain the spatial and spectral three-dimensional imaging of substances simultaneously, and obtain the unique continuous characteristic spectrum of substances in a wide spectrum range at a certain spatial resolution, which has outstanding advantages in the fine classification and identification of biological substances. With the development of hyperspectral imaging technology, a large amount of data has been accumulated in the exploration of data acquisition, image processing and material inspection. As a new technology means, hyperspectral imaging technology has its unique advantages and wide application prospects. It can be combined with the common biological physical evidence of blood (stains), saliva, semen, sweat, hair, nails, bones, etc., to achieve rapid separation, inspection and identification of substances. This paper introduces the basic theory of hyperspectral imaging technology and its application in common biological evidence examination research and analyzes the feasibility and development of biological evidence testing and identification, in order to provide a theoretical basis for the development of new technology and promote hyperspectral imaging technology in related biological examination, to better serve the forensic practice.
Spectrum Analysis/methods* ; Hyperspectral Imaging ; Forensic Medicine ; Blood Stains ; Technology