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.

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.

Objective To explore the reliability and safety of continuous monitoring of vital signs in patients using wireless wearable monitoring devices after video-assisted thoracoscopic surgery (VATS) for lung cancer. Methods The patients undergoing VATS for lung cancer in West China Hospital, Sichuan University from May to August 2023 were prospectively enrolled. Both wireless wearable and traditional wired devices were used to monitor the vital signs of patients after surgery. Spearman correlation analysis, paired sample t test and ratio Bland-Altman method were used to test the correlation, difference and consistency of monitoring data measured by the two devices. The effective monitoring rate of the wireless wearable device within 12 hours was calculated to test the reliability of its continuous monitoring. Results A total of 20 patients were enrolled, including 15 females and 5 males with an average age of 46.20±11.52 years. Data collected by the two monitoring devices were significantly correlated (P<0.001). Respiratory rate and blood oxygen saturation data collected by the two devices showed no statistical difference (P>0.05), while heart rate measured by wireless wearable device was slightly lower (=−0.307±1.073, P<0.001), and the blood pressure (=1.259±5.354, P<0.001) and body temperature(=0.115±0.231, P<0.001) were slightly higher. The mean ratios of heart rate, respiratory rate, blood oxygen saturation, blood pressure and body temperature collected by the two devices were 0.996, 1.004, 1.000, 1.014, and 1.003, respectively. The 95% limits of agreement (LoA) and 95% confidence interval of 95%LoA of each indicator were within the clinically acceptable limit. The effective monitoring rate of each vital signs within 12 hours was above 98%. Conclusion The wireless wearable device has a high accuracy and reliability for continuous monitoring vital signs of patients after VATS for lung cancer, which provides a security guarantee for subsequent large-scale clinical application and further research.

Aim To investigate the effect of Xuefu Zhuyu decoction on transforming growth factor-β1(TGF-β1 ) -induced endothelial-to-mesenchymal transition (EndMT) of pulmonary microvascular endothelial cells ( PMVEC), and further analyze the mechanism related to the TGF-β1/Smad signaling pathway. Method To construct an EndMT cell model, PMVEC was treated with TGF-β1 (5 μg · L

Sesquiterpenes are natural terpenoids with 15 carbon atoms in the basic skeleton, which mainly exist in plant volatile oil and have important physiological and medicinal value. Cytochrome P450 (CYP450) is a kind of monooxygenase encoded by supergene family, which is one of the largest gene families in plants. It is involved in the synthesis and metabolism of terpenoids, alkaloids and other secondary metabolites. In the process of terpene biosynthesis, CYP450 participates in the post-modification stage of terpenes by introducing functional groups such as hydroxyl, carboxyl and carbonyl, which plays an important role in enriching the diversity of terpenes. The CYP450 enzymes involved in sesquiterpene synthesis and their substrate catalytic specificity mechanisms have been partially investigated. In this paper, the biosynthetic pathway of plant sesquiterpenes, the structure and classification of CYP450 enzymes were briefly introduced, and the CYP450 enzymes involved in sesquiterpene biosynthesis were summarized, in order to provide a reference for intensive study of the role of CYP450 enzymes in the synthesis of sesquiterpenoids.

Small-molecule phenolic substances widely exist in animals and plants, and have some shared biological activities. The metabolism of phenylalanine and tyrosine in the human body, and especially the metabolism of catecholamine neurotransmitters, produces endogenous small-molecule phenols. Endogenous small-molecule phenolic substances are functionally related to the important physiological processes and the occurrence of mental diseases in humans and some animals, which are systematically sorts and summarized in this review. Integrating the previous experimental research and literature analysis on natural small-molecule phenols by our research group, the understanding of the hypothesis that "small-molecule phenol are pharmacological signal carriers" was deepened. Based on above, the concept of "phenolomics" was further proposed, analyzed the research direction and research content which can bring into the knowledge framework of phenolomics. The induction of phenolomics will provide wider perspectives on explaining the pharmacological mechanism of drugs, discovering new drug targets, and finding biomarkers of mental diseases.

This study aims to investigate the effect of salvianolic acid B (Sal B), the active ingredient of Salvia miltiorrhiza, on H9C2 cardiomyocytes injured by oxygen and glucose deprivation/reperfusion (OGD/R) through regulating mitochondrial fission and fusion. The process of myocardial ischemia-reperfusion injury was simulated by establishing OGD/R model. The cell proliferation and cytotoxicity detection kit (cell counting kit-8, CCK-8) was used to detect cell viability; the kit method was used to detect intracellular reactive oxygen species (ROS), total glutathione (t-GSH), nitric oxide (NO) content, protein expression levels of mitochondrial fission and fusion, apoptosis-related detection by Western blot. Mitochondrial permeability transition pore (MPTP) detection kit and Hoechst 33342 fluorescence was used to observe the opening level of MPTP, and molecular docking technology was used to determine the molecular target of Sal B. The results showed that relative to control group, OGD/R injury reduced cell viability, increased the content of ROS, decreased the content of t-GSH and NO. Furthermore, OGD/R injury increased the protein expression levels of dynamin-related protein 1 (Drp1), mitofusions 2 (Mfn2), Bcl-2 associated X protein (Bax) and cysteinyl aspartate specific proteinase 3 (caspase 3), and decreased the protein expression levels of Mfn1, increased MPTP opening level. Compared with the OGD/R group, it was observed that Sal B had a protective effect at concentrations ranging from 6.25 to 100 μmol·L^-1. Sal B decreased the content of ROS, increased the content of t-GSH and NO, and Western blot showed that Sal B decreased the protein expression levels of Drp1, Mfn2, Bax and caspase 3, increased the protein expression level of Mfn1, and decreased the opening level of MPTP. In summary, Sal B may inhibit the opening of MPTP, reduce cell apoptosis and reduce OGD/R damage in H9C2 cells by regulating the balance of oxidation and anti-oxidation, mitochondrial fission and fusion, thereby providing a scientific basis for the use of Sal B in the treatment of myocardial ischemia reperfusion injury.

Objective To understand the respiratory protection competency of staff in hospitals.Methods Staff from six hospitals of different levels and characteristics in Beijing were selected,including doctors,nurses,medical technicians,and servicers,to conduct knowledge assessment on respiratory protection competency.According to exposure risks of respiratory infectious diseases,based on actual cases and daily work scenarios,content of respira-tory protection competency assessment was designed from three aspects:identification of respiratory infectious di-seases,transmission routes and corresponding protection requirements,as well as correct selection and use of masks.The assessment included 6,6,and 8 knowledge points respectively,with 20 knowledge points in total,all of which were choice questions.For multiple-choice questions,full marks,partial marks,and no mark were given respective-ly if all options were correct,partial options were correct and without incorrect options,and partial options were correct but with incorrect options.Difficulty and discrimination analyses on question of each knowledge point was conducted based on classical test theory.Results The respiratory protection competency knowledge assessment for 326 staff members at different risk levels in 6 hospitals showed that concerning the 20 knowledge points,more than 60％participants got full marks for 6 points,while the proportion of full marks for other questions was relatively low.Less than 10％participants got full marks for the following 5 knowledge points:types of airborne diseases,types of droplet-borne diseases,conventional measures for the prevention and control of healthcare-associated infec-tion with respiratory infectious diseases,indications for wearing respirators,and indications for wearing medical protective masks.Among the 20 knowledge questions,5,1,and 14 questions were relatively easy,medium,and difficult,respectively;6,1,4,and 9 questions were with discrimination levels of ≥0.4,0.30-0.39,0.20-0.29,and ≤0.19,respectively.Conclusion There is still much room for hospital staff to improve their respiratory protection competency,especially in the recognition of diseases with different transmission routes and the indications for wearing different types of masks.