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

The gut microbiota regulates intestinal nutrient absorption, participates in modulating host glucolipid metabolism, and contributes to ameliorating glucolipid metabolism disorder. Dysbiosis of the gut microbiota can compromise the integrity of the intestinal mucosal barrier, induce inflammatory responses, and exacerbate insulin resistance and abnormal lipid metabolism in the host. Dangua Humai Oral Liquid, a hospital-developed formulation for regulating glucolipid metabolism, has been granted a national invention patent and demonstrates significant clinical efficacy. This study aimed to investigate the effects of Dangua Humai Oral Liquid on gut microbiota and the intestinal mucosal barrier in a mouse model with glucolipid metabolism disorder. A glucolipid metabolism disorder model was established by feeding mice a high-glucose and high-fat diet. The mice were divided into a normal group, a model group, and a treatment group, with eight mice in each group. The treatment group received a daily gavage of Dangua Humai Oral Liquid(20 g·kg~(-1)), while the normal group and model group were given an equivalent volume of sterile water. After 15 weeks of intervention, glucolipid metabolism, intestinal mucosal barrier function, and inflammatory responses were evaluated. Metagenomics and untargeted metabolomics were employed to analyze changes in gut microbiota and associated metabolic pathways. Significant differences were observed between the indicators of the normal group and the model group. Compared with the model group, the treatment group exhibited marked improvements in glucolipid metabolism disorder, alleviated pathological damage in the liver and small intestine tissue, elevated expression of recombinant claudin 1(CLDN1), occluding(OCLN), and zonula occludens 1(ZO-1) in the small intestine tissue, and reduced serum levels of inflammatory factors lipopolysaccharides(LPS), lipopolysaccharide-binding protein(LBP), interleukin-6(IL-6), and tumor necrosis factor-α(TNF-α). At the phylum level, the relative abundance of Bacteroidota decreased, while that of Firmicutes increased. Lipid-related metabolic pathways were significantly altered. In conclusion, based on the successful establishment of the mouse model of glucolipid metabolism disorder, this study confirmed that Dangua Humai Oral Liquid effectively modulates gut microbiota and mucosal barrier function, reduces serum inflammatory factor levels, and regulates lipid-related metabolic pathways, thereby ameliorating glucolipid metabolism disorder.
Animals ; Gastrointestinal Microbiome/drug effects* ; Mice ; Intestinal Mucosa/microbiology* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Mice, Inbred C57BL ; Humans ; Glycolipids/metabolism* ; Lipid Metabolism/drug effects* ; Administration, Oral ; Disease Models, Animal

OBJECTIVE: To explore the therapeutic effects and underlying mechanisms of Dendrobium officinale (Tiepi Shihu) extract (DOE) on insomnia. METHODS: Forty-two male Sprague-Dawley rats were randomly divided into 6 groups (n=7 per group): normal control, model control, melatonin (MT, 40 mg/kg), and 3-dose DOE (0.25, 0.50, and 1.00 g/kg) groups. Rats were raised in a strong-light (10,000 LUX) and -noise (>80 db) environment (12 h/d) for 16 weeks to induce insomnia, and from week 10 to week 16, MT and DOE were correspondingly administered to rats. The behavior tests including sodium pentobarbital-induced sleep experiment, sucrose preference test, and autonomous activity test were used to evaluate changes in sleep and emotions of rats. The metabolic-related indicators such as blood pressure, blood viscosity, blood glucose, and uric acid in rats were measured. The pathological changes in the cornu ammonis 1 (CA1) region of rat brain were evaluated using hematoxylin and eosin staining and Nissl staining. Additionally, the sleep-related factors gamma-aminobutyric acid (GABA), glutamate (GA), 5-hydroxytryptamine (5-HT), and interleukin-6 (IL-6) were measured using enzyme linked immunosorbent assay. Finally, we screened potential sleep-improving receptors of DOE using polymerase chain reaction (PCR) array and validated the results with quantitative PCR and immunohistochemistry. RESULTS: DOE significantly improved rats' sleep and mood, increased the sodium pentobarbital-induced sleep time and sucrose preference index, and reduced autonomic activity times (P<0.05 or P<0.01). DOE also had a good effect on metabolic abnormalities, significantly reducing triglyceride, blood glucose, blood pressure, and blood viscosity indicators (P<0.05 or P<0.01). DOE significantly increased the GABA content in hippocampus and reduced the GA/GABA ratio and IL-6 level (P<0.05 or P<0.01). In addition, DOE improved the pathological changes such as the disorder of cell arrangement in the hippocampus and the decrease of Nissel bodies. Seven differential genes were screened by PCR array, and the GABA_A receptors (Gabra5, Gabra6, Gabrq) were selected for verification. The results showed that DOE could up-regulate their expressions (P<0.05 or P<0.01). CONCLUSION DOE demonstrated remarkable potential for improving insomnia, which may be through regulating GABA_A receptors expressions and GA/GABA ratio.
Animals ; Dendrobium/chemistry* ; Rats, Sprague-Dawley ; Male ; Sleep Initiation and Maintenance Disorders/blood* ; Plant Extracts/therapeutic use* ; Receptors, GABA-A/metabolism* ; Noise/adverse effects* ; Light/adverse effects* ; gamma-Aminobutyric Acid/metabolism* ; Sleep/drug effects* ; Rats ; Receptors, GABA/metabolism*

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

In China, the crude oil supply is highly dependent on overseas countries, and thus strengthening crude oil self-sufficiency has become an important issue of the national energy security. Tertiary oil recovery, especially polymer flooding, has been widely applied in large oil fields in China, which can increase the recovery rate by 15%-20% compared with water flooding. However, the widely used oil flooding polymers show poor thermal stability and salinity tolerance, complicated synthesis ways of monomers, and environmental unfriendliness. Moreover, the polymer flooding induces problems including pore plugging, heterogeneity intensification, high dispersion of remaining oil resources, pressure rise in injection wells, and low efficiency circulation of injection medium, which restrict the subsequent recovery of old oil fields. Here, we systematically review the developing and current situations of polymer flooding, introduce the innovative biomanufacturing of oil flooding polymers and their monomers or precursors as well as low-cost bio-based chemical raw materials for multiple compound flooding. The comprehensive study of the relationships between microbial fermentation metabolites and polymer flooding will reveal the green and low-carbon paths for polymer flooding. Such study will enable the application of enzymes produced by microorganisms in polymer production and polymer plugging removal after polymer flooding as well as the application of microbial metabolites such as biosurfactants, organic acids, alcohols, biogas, and amino acids in enhancing oil recovery. This review suggests that incorporating biomanufacturing into polymer flooding will ensure the high productivity and stability for crude oil production in China.
Polymers/metabolism* ; China ; Petroleum ; Oil and Gas Fields

Background::Findings on the association of genetic factors and colorectal cancer (CRC) survival are limited and inconsistent, and revealing the mechanism underlying their prognostic roles is of great importance. This study aimed to explore the relationship between functional genetic variations and the prognosis of CRC and further reveal the possible mechanism.Methods::We first systematically performed expression quantitative trait locus (eQTL) analysis using The Cancer Genome Atlas (TCGA) dataset. Then, the Kaplan-Meier analysis was used to filter out the survival-related eQTL target genes of CRC patients in two public datasets (TCGA and GSE39582 dataset from the Gene Expression Omnibus database). The seven most potentially functional eQTL single nucleotide polymorphisms (SNPs) associated with six survival-related eQTL target genes were genotyped in 907 Chinese CRC patients with clinical prognosis data. The regulatory mechanism of the survival-related SNP was further confirmed by functional experiments.Results::The rs71630754 regulating the expression of endoplasmic reticulum aminopeptidase 1 ( ERAP1) was significantly associated with the prognosis of CRC (additive model, hazard ratio [HR]: 1.43, 95% confidence interval [CI]: 1.08-1.88, P = 0.012). The results of dual-luciferase reporter assay and electrophoretic mobility shift assay showed that the A allele of the rs71630754 could increase the binding of transcription factor 3 (TCF3) and subsequently reduce the expression of ERAP1. The results of bioinformatic analysis showed that lower expression of ERAP1 could affect the tumor immune microenvironment and was significantly associated with severe survival outcomes. Conclusion::The rs71630754 could influence the prognosis of CRC patients by regulating the expression of the immune-related gene ERAP1. Trial Registration::No. NCT00454519 (https://clinicaltrials.gov/)

Rhino-orbito-cerebral mucormycosis (ROCM) is an acute, rapidly progressive, and lethal opportunistic fungal disease. Due to the atypical clinical manifestations, the disease is easily misdiagnosed in the early stage. The patients with ROCM associated cerebrovascular complications generally have a high mortality rate. This article reports a 47-year-old female patient with diabetic ketoacidosis and COVID-19 admitted to Central Hospital Affiliated to Shandong First Medical University. The results of radiological examinations and cerebrospinal fluid metagenomic next-generation sequencing confirmed as Rhizopus oryzae associated ROCM. In spite of receiving amphotericin B colloidal dispersion and isavuconazole treatments, the patient died of ROCM complicated with severe cerebral infarctions and pulmonary infection. The purpose of this case report is to summarize the clinical characteristics of ROCM with cerebrovascular ischemic events and the rare condition of bilateral anterior circulation involvements, and introduce recent diagnostic and therapeutic approaches for this disease.

Objective:To investigate the iodine nutritional status of children and the consumption condition of non-iodized salt in Henan Province after implementation of the new standard of "Definition and demarcation of water-borne iodine-excess areas and iodine-excess endemial areas" (GB/T 19380-2016, hereinafter referred to as new standard) for four years (2021), and to provide a basis for scientific adjustment of intervention strategies.Methods:In 2021, according to the requirements of the new standard and based on the results of the water iodine survey in Henan Province from 2017 to 2020, a survey was conducted on the iodine nutrition status of children in water-borne high iodine areas in 47 counties (cities, districts, hereinafter referred to as counties) with high iodine administrative village (neighborhood committee, hereinafter referred to as administrative village). In each county, 5 administrative villages with median water iodine > 100 μg/L were selected as the investigation villages, and water samples were collected to determine the water iodine value. Forty non-boarding students aged 8 - 10 (age balanced, half male and half female, age increased to 6 - 12 when less than 40) were selected from each village as investigation subjects. Salt samples from their homes and urine samples were collected to detect salt iodine and urine iodine content, and thyroid volume of children was measured. And the monitoring results of areas where the supply of iodized salt had been suspended for less than 4 years (in newly high iodine areas) and more than 10 years (in previously high iodine areas) were further compared and analyzed.Results:A total of 257 administrative villages in the province were monitored, and the range of water iodine was 1.6 - 609.5 μg/L, with a median of 132.5 μg/L. A total of 8 611 children were tested for salt iodine, urine iodine and thyroid volume. The non-iodized salt rate was 58.3% (5 017/8 611), and the median urine iodine was 342.2 μg/L, thyroid enlargement rate was 2.9% (250/8 611). The median water iodine (153.0 vs 118.4 μg/L), the median urine iodine in children (371.6 vs 287.7 μg/L) and the goiter rate [3.8% (211/5 537) vs 1.3% (39/3 074)] in the newly high iodine areas were higher than those in the previously high iodine areas, and the differences were statistically significant ( Z = 583.12, - 14.09, P < 0.001; χ 2 = 44.40, P < 0.001); the non-iodized salt rate was lower than that of the previously high iodine areas [37.2% (2 057/5 537) vs 96.3% (2 960/3 074)], and the difference was statistically significant (χ 2 = 2 841.37, P < 0.001). Conclusions:The iodine nutrition level of children in water-borne high iodine areas of Henan Province in 2021 is at an excess level, but the non-iodized salt rate in residential households is low. We should make every effort to ensure the precise supply of non-iodized salt in high iodine areas after implementation of the new standard, and strengthen iodine nutrition monitoring and health education for key populations to prevent the occurrence of high iodine hazards.