In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

OBJECTIVE: To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures. METHODS: Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details. RESULTS: Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters. CONCLUSION Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans ; Male ; Female ; Radius Fractures/surgery* ; Middle Aged ; Adult ; Aged ; Aged, 80 and over ; Tomography, X-Ray Computed/methods* ; Retrospective Studies ; Software ; Wrist Fractures

Human NAD(P)H: quinone oxidoreductase 1 (NQO1) is a flavoenzyme expressed at high levels in multiple solid tumors, making it an attractive target for anticancer drugs. Bioactivatable drugs targeting NQO1, such as β-lapachone (β-lap), are currently in clinical trials for the treatment of cancer. β-Lap selectively kills NQO1-positive (NQO1⁺) cancer cells by inducing reactive oxygen species (ROS) via catalytic activation of NQO1. In this study, we demonstrated that cryptotanshinone (CTS), a naturally occurring compound, induces NQO1-dependent necrosis without affecting NQO1 activity. CTS selectively kills NQO1⁺ cancer cells by inducing NQO1-dependent necrosis. Interestingly, CTS directly binds to NQO1 but does not activate its catalytic activity. In addition, CTS enables activation of JNK1/2 and PARP, accumulation of iron and Ca²⁺, and depletion of ATP and NAD⁺. Furthermore, CTS selectively suppressed tumor growth in the NQO1⁺ xenograft models, which was reversed by NQO1 inhibitor and NQO1 shRNA. In conclusion, CTS induces NQO1-dependent necrosis via the JNK1/2/iron/PARP/NAD⁺/Ca²⁺ signaling pathway. This study demonstrates the non-enzymatic function of NQO1 in inducing cell death and provides new avenues for the design and development of NQO1-targeted anticancer drugs.

Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*

OBJECTIVE: To develop and compare risk prediction models for in-hospital post-cardiac arrest brain injury (PCABI) in critically ill patients using nomograms and random forest algorithms, aiming to identify the optimal model for early identification of high-risk PCABI patients and providing evidence for precise treatment. METHODS: A retrospective cohort study was used to collect the first-time in-hospital cardiac arrest (IHCA) patients admitted to the intensive care unit (ICU) from 2008 to 2019 in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) as the study population, and the patients' age, gender, body mass, health insurance utilization, first vital signs and laboratory tests within 24 hours of ICU admission, mechanical ventilation, and critical care scores were extracted. Independent influencing factors of PCABI were identified through univariate and multivariate Logistic regression analyses. The included patients were randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio, and the PCABI risk prediction model was constructed by the nomogram and random forest algorithm, respectively, and the model was evaluated by receiver operator characteristic curve (ROC curve), the calibration curve, and the decision curve analysis (DCA), and after the better model was selected, 179 patients admitted to Tianjin Medical University General Hospital as the external validation cohort for external evaluation were collected by using the same inclusion and exclusion criteria. RESULTS: A total of 1 419 patients with without traumatic brain injury who had their first-time IHCA were enrolled, including 995 in the training cohort (including 176 PCABI and 819 non-PCABI) and 424 in the internal validation cohort (including 74 PCABI and 350 non-PCABI). Univariate and multivariate analysis showed that age, potassium, urea nitrogen, sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation III (APACHE III), and mechanical ventilation were independent influences on the occurrence of PCABI in patients with IHCA (all P < 0.05). Combining the above variables, we constructed a nomogram model and a random forest model for comparison, and the results show that the nomogram model has better predictive efficacy than the random forest model [nomogram model: area under the ROC curve (AUC) of the training cohort = 0.776, with a 95% credible interval (95%CI) of 0.741-0.811; internal validation cohort AUC = 0.776, with a 95%CI of 0.718-0.833; random forest model: AUC = 0.720, with a 95%CI of 0.653-0.787], and they performed similarly in terms of calibration curves, but the nomogram performed better in terms of decision curve analysis (DCA); at the same time, the nomogram model was robust in terms of external validation cohort (external validation cohort AUC = 0.784, 95%CI was 0.692-0.876). CONCLUSIONS A nomogram risk prediction model for the occurrence of PCABI in critically ill patients was successfully constructed, which performs better than the random forest model, helps clinicians to identify the risk of PCABI in critically ill patients at an early stage and provides a theoretical basis for early intervention.
Humans ; Critical Illness ; Retrospective Studies ; Heart Arrest/complications* ; Nomograms ; Brain Injuries/etiology* ; Intensive Care Units ; Algorithms ; Male ; Female ; Middle Aged ; ROC Curve ; Risk Factors ; Risk Assessment ; Logistic Models ; Aged

Objective:To study the serological characteristics of ABO*A2.08 subtype and explore its genetic molecular mechanism.Methods:ABO blood group identification was performed on proband and her family members by routine serological methods.ABO genotyping and sequence analysis were performed by polymerase chain reaction-sequence specific primer(PCR-SSP),and direct sequencing of PCR products from exons 6 and 7 of ABO gene were directly sequenced and analyzed.The effect of gene mutation in A2.08 subtype on structural stability of GTA protein was investigated by homologous protein conserved analysis,3D molecular modeling and protein stability prediction.Results:The proband's serological test results showed subtype Ax,and ABO genotyping confirmed that the proband's genotype was ABO*A207/08.Gene sequencing of the proband's father confirmed the characteristic variation of c.539G＞C in the 7th exon of ABO gene,leading to the replacement of polypeptide chain p.Arg180Pro(R180P).3D protein molecular modeling and analysis suggested that the number of hydrogen bonds of local amino acids in the protein structure was changed after the mutation,and protein stability prediction showed that the mutation had a great influence on the protein structure stability.Conclusion:The mutation of the 7th exon c.539G＞C of ABO gene leads to the substitution of polypeptide chain amino acid,which affects the structural stability of GTA protein and leads to the change of enzyme activity,resulting in the A2.08 phenotype.The mutated gene can be stably inherited.

Objective:To make a quantitative analysis of the policy tools of 261 prefectural-level basic medical insurance risk pooling policy text,analyze the distribution characteristics in dimensions including phases,tools and objectives,so as to provide references for the optimization of China's basic medical insurance risk pooling policy.Methods:Content analysis and quantitative analysis method were performed,a three-dimensional framework of"tools(X-dimension)-objectives(Y-dimension)-phases(Z-dimension)"was constructed,which was used to perform multi-dimensional classification and cross-comparison analysis on policy items.Results:According to the X-dimension,environmental and demand-based policy tools were constantly improving,but partial policy sub-tools are seriously missing.From the Y-dimension,policy objectives covered multiple dimensions but failed to complement each other.From the Z-dimension,the use of policy tools in different stages shows the characteristics of gradual progressive and hierarchical diffusion.policy suggestions are put forward:Optimize the combination of various policy tools,improve the adaptability of policy content and objectives,and form inter-dimensional policy synergy.On the basis of the summarized experience in the application of policy tools,providing references for provincial-level basic medical insurance risk pooling in China.

Objective:To investigate the relationship and clinical significance of circulating tu-mor DNA(ctDNA)methylation with postoperative recurrence of thyroid cancer.Method:5 pa-tients with recurrent thyroid cancer in our hospital from March 2021 to April 2022 were selected as the observation group,and 2 healthy volunteers were selected as the control group.The level of ctDNA methylation in peripheral blood of the two groups was detected by Illumina high-throughput sequencing system.Gene ontology(GO)function analysis and Kyoto gene and genome encyclope-dia(KEGG)signal pathway analysis were carried out on the methylation region genes with signifi-cant differences through the DAVID gene function analysis platform.Result:There were 7787 dif-ferential ctDNA methylation sites between the two groups.2914(37.4％)were hypermethylation sites and 4873(62.6％)were low methylation sites.GO functional analysis showed that differentially methylated genes were enriched in molecular functions such as DNA-binding transcriptional acti-vation,cell-substrate adhesion,glycoprotein complex and other cellular components.KEGG path-way analysis showed that differentially methylated genes were enriched in thyroid carcinoma signal pathway,cell adhesion molecules,RAP1 signal pathway,RAS signal pathway,MAPK signal path-way and so on.Conclusion:ctDNA methylation may be involved in cancer recurrence in postop-erative patients with thyroid cancer.Monitoring the level of ctDNA methylation in peripheral blood may be an effective method to indicate the recurrence or metastasis of thyroid cancer and guide clinical diagnosis and treatment.

Alcohol abuse is a serious public health problem and biomedical safety problem that can lead to a variety of neuropsychiatric disorders. In recent years, numerous studies have shown that alcohol can induce structural and functional disregulation in the basolateral amygdala (BLA). Alcohol exposure and withdrawal can cause negative emotion such as anxiety and fear, primarily mediated by glutamatergic neurons and inhibitory γ-aminobutyric acid ergic(GABAergic) interneurons in the BLA. Glutamatergic neurons are responsible for excitatory neurotransmitter glutamate release, while γ-aminobutyric acid ergic(GABAergic) interneurons provide feedback inhibition to suppress BLA function and alleviate negative emotions. However, alcohol intake can disrupt the balance of glutamatergic-GABAergic neural network, altering neuron excitability and subsequently leading to the generation of anxiety and fear. Moreover, alcohol also interferes with the corticotropin-releasing factor(CRF) system within the BLA, increasing the release of CRF, further stimulating anxiety-related emotions. Additionally, alcohol affects BLA-related neural circuits, such as BLA →medial prefrontal cortex, BLA →nucleus accumbens, and BLA →bed nucleus of the stria terminali pathways, thereby impacting anxiety-like behaviors.This review discusses the progress of neural signaling and circuits within the BLA in mediating alcohol-induced negative emotions, aiming to further elucidate the neurobiological mechanisms underlying anxiety triggered by alcohol exposure and withdrawal, in order to provide theoretical basis for clinical treatment in the future.

Objective To explore the effect of Qingre Xiaoyanning tablets on chronic toxicity in SD rats.Methods A total of 120 SD rats were randomly divided into blank group(water)and experimental-L,-M,-H groups(2.63,5.25 and 10.50 g·kg 1 Qingre Xiaoyanning dry paste powder),with 30 rats per group.Four groups were administered continuously for 4 weeks with a recovery period of 4 weeks.SD rats were dissected as planned.The general condition,weight gain,hematological and biochemical indexes,major organ coefficients,macroscopic and microscopic tissue morphology were observed.Results There were no significant differences in the general condition,body mass growth,coagulation index and histopathology of rats between the experimental-L,-M,-H groups and the blank group.End of administration,the mean hemoglobin concentrations of experimental-H and blank groups were(370.70±3.78)and(365.90±5.77)g·L-1,glucose were(5.98±0.63)and(6.61±0.93)mmol·L-1,blood urea nitrogen(BUN)were(4.72±1.01)and(5.78±1.64)mmol·L-1,liver coefficients were 3.05±0.17 and 2.89±0.19,and the differences were statistically significant(P≤0.05,P≤0.01).Resumption of the final,direct bilirubin of experimental-L and blank groups were(0.38±0.18)and(0.19±0.18)pmol·L 1,BUN of experimental-M and blank groups were(4.45±0.56)and(5.65±1.16)mmol·L-1,and the differences were statistically significant(all P≤0.05).Conclusion Repeated administration of Qingre Xiaoyanning tablets showed no significant toxicity in SD rats.