ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

ObjectiveTo establish the multi-technique characteristic profiles of Alumen by X-ray diffraction（XRD）， Fourier-transform infrared spectroscopy（FTIR） and thermogravimetric-differential thermal analysis（TG-DTA）， and to explore the spectral characteristics for rapid identification of Alumen and its potential adulterant， Ammonium alum. MethodsA total of 27 batches of Alumen samples from 8 production regions were collected for preliminary identification based on visual characteristics. The PDF standard cards of XRD were used to differentiate Alumen from A. alum， and the XRD characteristic profiles of Alumen were established， and then the common peaks were screened. Based on hierarchical clustering analysis（HCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）， the characteristic information that could be used for identification of Alumen was selected with variable importance in the projection（VIP） value>1. FTIR characteristic profiles of Alumen were established， and key wavenumbers for identification were screened by HCA and OPLS-DA with VIP value>1. Meanwhile， the thermogravimetric differences between Alumen and A. alum were analyzed by TG-DTA， and the thermogravimetric traits that could be used for identification were screened. ResultsAlumen and A. alum could not be effectively distinguished by traits alone. However， by comparing the PDF standard cards of XRD， 15 batches of Alumen and 12 batches of A. alum could be distinguished. In the XRD profiles， 10 characteristic peaks were confirmed， corresponding to diffraction angles of 14.560°， 24.316°， 12.620°， 32.122°， 17.898°， 34.642°， 27.496°， 46.048°， 40.697° and 21.973°. In the FTIR profiles， 4 wavenumber ranges（399.193-403.050， 1 186.010-1 471.420， 1 801.190-2 620.790， 3 612.020-3 997.710 cm^-1） and 12 characteristic wavenumbers（1 428.994， 1 430.922， 1 432.851， 1 434.779， 1 436.708， 1 438.636， 1 440.565， 1 442.493， 1 444.422， 1 446.350， 1 448.279， 1 450.207 cm^-1） were identified. In the TG-DTA profiles， there were characteristic decomposition peaks of ammonium ion and mass reduction features near 555.34 ℃ for A. alum. These characteristics could serve as important criteria for distinguishing the authenticity of Alumen. ConclusionXRD， FTIR and TG-DTA can be used to rapidly detect Alumen and A. alum， and combined with the discriminant features selected through chemometrics， the rapid and accurate identification of Alumen and A. alum can be achieved. The research findings provide new approaches for the rapid identification of Alumen.

Guided by the concept of quality by design(QbD), this study optimizes the calcination and quenching process of calcined Magnetitum and establishes the XRD characteristic spectra of calcined Magnetitum, providing a scientific basis for the formulation of quality standards. Based on the processing methods and quality requirements of Magnetitum in the Chinese Pharmacopoeia, the critical process parameters(CPPs) identified were calcination temperature, calcination time, particle size, laying thickness, and the number of vinegar quenching cycles. The critical quality attributes(CQAs) included Fe mass fraction, Fe~(2+) dissolution, and surface color. The weight coefficients were determined by combining Analytic Hierarchy Process(AHP) and the criteria importance though intercrieria correlation(CRITIC) method, and the calcination process was optimized using orthogonal experimentation. Surface color was selected as a CQA, and based on the principle of color value, the surface color of calcined Magnetitum was objectively quantified. The vinegar quenching process was then optimized to determine the best processing conditions. X-ray diffraction(XRD) was used to establish the characteristic spectra of calcined Magnetitum, and methods such as similarity evaluation, cluster analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to evaluate the quality of the spectra. The optimized calcined Magnetitum preparation process was found to be calcination at 750 ℃ for 1 h, with a laying thickness of 4 cm, a particle size of 0.4-0.8 cm, and one vinegar quenching cycle(Magnetitum-vinegar ratio 10∶3), which was stable and feasible. The XRD characteristic spectra analysis method, featuring 9 common peaks as fingerprint information, was established. The average correlation coefficient ranged from 0.839 5-0.988 1, and the average angle cosine ranged from 0.914 4 to 0.995 6, indicating good similarity. Cluster analysis results showed that Magnetitum and calcined Magnetitum could be grouped together, with similar compositions. OPLS-DA discriminant analysis identified three key characteristic peaks, with Fe_2O_3 being the distinguishing component between the two. The final optimized processing method is stable and feasible, and the XRD characteristic spectra of calcined Magnetitum was initially established, providing a reference for subsequent quality control and the formulation of quality standards for calcined Magnetitum.
X-Ray Diffraction/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Particle Size

This study explored the active ingredients for anti-angiogenesis in Wenyujin Rhizoma Concisum. Ten sesquiterpenoids were isolated from Wenyujin Rhizoma Concisum by silica gel column chromatography, thin layer chromatography, and high performance liquid chromatography. According to the results of multiple spectroscopic methods and circular dichroism, they were identified as wenyujinlactam A(1),(4S,7S)11-hydroxycurdione(2), 8,9-seco-4β-hydroxy-1α,5βH-7(11)-guaen-8,10-olide(3), curcumadione(4), phaeocaulisin E(5), procurcumadiol(6), zedouronediol(7), epiprocurcumenol(8), gajutsulactone A(9), and(7Z)-1β,4α-dihydroxy-5α,8β(H)-eudesm-7(11)-en-8,12-olide(10). Compounds 1 and 2 were new sesquiterpenoids. Compounds 1, 6, 8, and 10 can inhibit human umbilical vein endothelial cells(HUVEC) proliferation with IC_(50) values of 38.83, 45.19, 32.12, and 37.80 μmol·L~(-1), respectively. Compounds 1 and 10 can inhibit HUVEC migration with IC_(50) values of 29.70 and 36.48 μmol·L~(-1), respectively.
Sesquiterpenes/isolation & purification* ; Humans ; Drugs, Chinese Herbal/isolation & purification* ; Rhizome/chemistry* ; Human Umbilical Vein Endothelial Cells/drug effects* ; Molecular Structure ; Cell Proliferation/drug effects*

Central sensitization(CS) is an important factor in inducing neuropathic pain(NPP), and the association between signal transduction protein 1(Epac1) and piezoelectric type mechanosensitive ion channel component 2(Piezo2) is a new and significant pathway for initiating CS. This study whether the central analgesic effect of Maxiong Powder is achieved through the synchronized regulation of the Epac1-Piezo2 signaling pathway in the medial habenular nucleus(MHb) and interpeduncular nucleus(IPN) of the brain. Dynamic in vivo microdialysis, combined with high-performance liquid chromatography-fluorescence detection(HPLC-RFC), behavioral assessments, immunohistochemistry, Western blot, and quantitative reverse transcription PCR, were employed in rats with partial sciatic nerve injury(SNI) to investigate the distribution and expression of Epac1 and Piezo2 proteins and genes in the MHb and IPN regions, and the changes in the extracellular levels of glutamate(Glu), aspartic acid(Asp), and glycine(Gly). Compared with the sham group, rats in the SNI group showed significantly reduced analgesic activity, a significant increase in cold pain sensitivity scores, and elevated Glu levels in the MHb and IPN regions. Additionally, the number of Piezo2-positive cells in these regions, as well as the expression levels of Epac1 and Piezo2 proteins and genes, were significantly increased. Compared with the SNI group, after Maxiong Powder administration, the analgesic activity in rats significantly increased, and cold pain sensitivity scores were significantly reduced. Maxiong Powder also significantly decreased the Glu content in the MHb and IPN regions and the Gly content in the MHb region, while significantly increasing the Asp content in both regions. Furthermore, Maxiong Powder significantly reduced the number of Piezo2-positive cells and lowered the protein and gene expression levels of Epac1 and Piezo2 in both brain regions. The central analgesic effect of Maxiong Powder may be related to its inhibition of Glu and Gly release in the extracellular fluid of the MHb and IPN regions, the increase of Asp levels in these regions, and the regulation of the Epac1-Piezo2 pathway through the reduction of Epac1 and Piezo2 protein and gene expression. These results provide partial scientific evidence for the clinical analgesic efficacy of Maxiong Powder and offer new ideas and approaches for the clinical treatment of NPP.
Animals ; Neuralgia/genetics* ; Rats ; Signal Transduction/drug effects* ; Male ; Rats, Sprague-Dawley ; Guanine Nucleotide Exchange Factors/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Habenula/drug effects* ; Ion Channels/genetics* ; Humans

This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

In this study, the pharmacodynamic components and potential pharmacological functions of Danzhi Xiaoyao Formula in treating nervous system diseases were investigated by hippocampal component characterization and network pharmacology. After rats were administrated with Danzhi Xiaoyao Formula by gavage, high performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry(HPLC-Q-TOF-MS/MS) was employed to explore the components in the hippocampus of rats. Fifty-seven components were identified in the hippocampus of rats by comparing the extract of Danzhi Xiaoyao Formula, herbal components in the hippocampus after administration, and blank samples. KEGG and GO analyses predicted 74 core targets including GSK3B, MAPK1, AKT, IL6. These targets were involved in PI3K/Akt, NF-κB, MAPK, JAK/STAT, Wnt, and other signaling pathways. The results indicated that Danzhi Xiaoyao Formula may ameliorate other nervous system diseases enriched in DO, such as neurodegenerative diseases, cerebrovascular diseases, and mental and emotional disorders by mediating target pathways, inhibiting inflammation, reducing neuronal damage, and alleviating hippocampal atrophy. The relevant activities exhibited by this formula in nervous system diseases such as Alzheimer's disease, Parkinson's disease, and diabetic neuropathy have extremely high development value and are worthy of further in-depth research. This study provides a theoretical basis and practical guidance for expanding the application of Danzhi Xiaoyao Formula in the treatment of nervous system diseases.
Drugs, Chinese Herbal/administration & dosage* ; Animals ; Rats ; Hippocampus/metabolism* ; Network Pharmacology ; Chromatography, High Pressure Liquid ; Tandem Mass Spectrometry ; Rats, Sprague-Dawley ; Male ; Nervous System Diseases/genetics* ; Humans ; Signal Transduction/drug effects*

Medicinal plant underground diseases, typified by root rot, directly result in a significant reduction in both the yield and quality of traditional Chinese medicine(TCM) because of its hidden occurrence and difficulty in prevention and control. Prevention and control measures depending on chemical pesticides bring potential risks to the safety of TCM and easily cause environmental pollution. The introduction of the new version of Good Agricultural Practice for Chinese Crude Drugs(GAP) and the enhancement of pesticide residue limit standards for TCM and decoction pieces in Chinese Pharmacopoeia(2025 edition) have elevated the requirements for green and efficient disease prevention and control technologies of TCM. This paper provided a comprehensive overview of the advancements over the past two decades in the diversity of pathogens, characteristics and hazards associated with disease occurrence, the main prevention and control agents currently registered, and the prevention and control techniques for TCM root rot. In light of the environmental backdrop of global climate change and the increasing frequency of disastrous climates, coupled with the challenges encountered in root rot prevention and control amidst the new paradigm of large-scale and standardized cultivation of TCM, the paper proposed the key direction of basic research and the application strategy for new technologies that integrate "early prevention and control-soil health-digital monitoring", including precise pathogen identification and early disease diagnosis, exploration of host disease resistance mechanisms and disease-resistant breeding, field soil health and ecological regulation, monitoring of fungicide resistance and rational pesticide use, as well as the integration of digital technology and intelligent plant protection. The ultimate goal is to advance the application of green plant protection technology in TCM, thereby providing robust scientific and technological support to ensure the healthy and sustainable development of the TCM agriculture sector.
Plant Diseases/microbiology* ; Plant Roots/microbiology* ; Plants, Medicinal/growth & development* ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Objective To analyze the evaluation and influencing factors of healthy enterprises in Hubei Province from 2020 to 2023. Methods A total of 351 enterprises participated in the healthy enterprise evaluation in Hubei province were selected as the study subjects using the judgmental sampling method. The differences in evaluation results including scales, industry sector, and ownership type of the enterprises were compared. Results The median and the 25th and 75th percentiles [M (P₂₅, P₇₅)] of the evaluation score among the 351 enterprises was 869 (838, 941) points. The evaluation pass rate was 82.3%. The M(P₂₅, P₇₅) of scores for the management system, health environment, health management and services, health culture, and health outcome review were 183 (174, 192), 190 (181, 198), 340 (321, 376), 133 (122, 142), and 26 (24, 28) points, with the score percentage of 91.5%, 86.4%, 85.0%, 88.7%, and 86.7%, respectively. The deduction rate exceeded 50.0% in six items, which predominantly concentrated within the primary indicator of the health management and services, among the tertiary indicators. The result of multiple linear regression analysis revealed that smaller enterprises had significantly lower evaluation scores (P<0.05), and domestically funded enterprises scored significantly lower than those with investment from Hong Kong, Macao and Taiwan, or foreign investments (all P<0.05). Conclusion Health management and services represent a weak area in healthy enterprise development in Hubei Province. It was suggested to improve policy incentives and support for medium-, small- and micro-sized enterprises, and domestically funded enterprises, to enhance healthy enterprise development levels.