With the rapid advancement of hemodynamic indices and monitoring technologies, their classification methods and application processes have become increasingly complex. Currently, no unified standard hasbeen established, making it difficult to fully meet the clinical requirements for hemodynamic management. To assist in hemodynamic monitoring assessment and therapeutic decision-making in critically ill patients, the Critical Hemodynamic Therapy Collaborative Group, in conjunction with the Critical Ultrasound Study Group, has jointly developed the Standard for the Application of Hemodynamic Monitoring Techniques in Critical Care. The first part of this standard systematically categorizes hemodynamic indicators into flow indicators, pressure and its derivative indicators, and tissue perfusion indicators, while elaborating on the clinical application of each. The second part establishes a standardized clinical implementation pathway for hemodynamic monitoring. It proposes a tiered monitoring strategy-comprising basic, advanced, indication-specific, and special scenario monitoring-tailored to different clinical settings. It emphasizes the central role of critical care ultrasound across all levels of monitoring and establishes hemodynamic assessment standards for organs such as the brain, kidneys, and gastrointestinal tract. This standard aims to provide a unified framework for clinical practice, teaching, training, and research in critical care medicine, thereby promoting standardized development within the discipline.

AIM: To explore the factors influencing heart rate(HR)changes during small incision lenticule extraction(SMILE)surgery by monitoring HR trends at different time points of the procedure.METHODS: Prospective cohort study. A total of 69 patients who underwent SMILE surgery at the Laser Vision Correction Center of Xi'an No.1 Hospital from April to May 2024 were enrolled. Before the surgery, patients completed the State Anxiety Inventory(S-AI, questions 1-20)to assess their preoperative anxiety scores related to the next day's surgery. Baseline HR was recorded using medical pulse oximeter, and real-time HR was recorded during patient positioning, lenticule scanning, lenticule separation and extraction, and the application of postoperative eye drops.RESULTS: The HR during patient positioning was 83.61±13.87 bpm, which was significantly different from the baseline HR(77.52±10.88 bpm), HR during lenticule separation and extraction(75.54±12.52 bpm), and HR during postoperative eye drop application(76.65±10.54 bpm; all P<0.001). When stratified by median age, older patients(>26 years)had the HR during lenticule separation and extraction 76.27±9.93 bpm, which differed from the HR at positioning(84.82±14.10 bpm)and at lens scanning(82.76±13.72 bpm; all P<0.005). Stratified by gender, the HR of male patients at positioning was the highest(85.31±16.61 bpm), which differed significantly from the baseline HR(78.26±12.63 bpm), HR during lenticule separation and extraction(77.14±14.59 bpm), and HR during postoperative eye drop application(77.11±12.49 bpm; all P<0.005). There was no correlation between HR during positioning and preoperative anxiety scores(r=0.124, P=0.418).CONCLUSION: HR changes during SMILE surgery vary with different procedural stages, peaking during patient positioning and reaching the lowest point during lenticule separation and extraction. Older patients showed higher HR during positioning, and male patients exhibited higher HR during positioning.

OBJECTIVE To establish fingerprint， chemical pattern recognition and multi-component quantification analysis of Sanzi powder， and evaluate its quality. METHODS HPLC method was adopted. The fingerprints of 15 batches of Sanzi powder were established by using the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （2012 edition）. Cluster analysis， principal component analysis and orthogonal partial least squares-discriminant analysis were also conducted. The variable importance in projection （VIP） value greater than 1 was used as the index to screen the differential markers， and the contents of the differential markers were determined by the same HPLC method. RESULTS A total of 21 common peaks in the HPLC fingerprints of 15 batches of Sanzi powder were calibrated， and the similarities of them were 0.994- 0.999； 6 common peaks were identified， including gallic acid （peak 3）， garminoside （peak 10）， corilagin （peak 11）， chebulinic acid （peak 16）， ellagic acid （peak 18）， crocin Ⅰ （peak 19）. According to the results of cluster analysis， YKD2024LH005，No.YKD2023LH062） principal component analysis and orthogonal partial least squares-discriminant analysis， 15 batches of samples could be clustered into two categories： S1， S5， S7， S9， S14 were clustered into one category； S2-S4， S6， S8， S10-S13， S15 were clustered into one category. VIP values of 11 differential components such as corilagin， chebulinic acid and ellagic acid were higher than 1. Among 15 batches of samples， the contents of corilagin， chebulinic acid and ellagic acid ranged 2.667-5.152， 9.506- 13.522， 0.891-1.811 mg/g. CONCLUSIONS Established HPLC fingerprint and multi-component quantification analysis of Sanzi powder are rapid and simple， and can be used for quality evaluation of Sanzi powder by combining with chemical pattern recognition. Eleven components such as corilagin， chebulinic acid and ellagic acid are differential markers affecting the quality of Sanzi powder.

As a cheap and effective antibiotic,sulfonamides are often used in animal husbandry.However,their residues in animal-derived foodstuffs will threaten human health.Consequently,a high-performance liquid chromatography(HPLC)method integrated with supramolecular solvent microextraction was successfully established for simultaneous quantification of sulfonamide residues sulfachlorpyridazine,sulfamethoxazole,sulfamethoxypyridazine and sulfadimethoxine in milk matrices.This approach exhibited prominent characteristics of operational simplicity,environmental sustainability,and high extraction efficiency.The supramolecular solvents prepared by tributyl octylphosphine tetrafluoroborate and tetrahydrofuran were employed as extraction solvents.The analytes underwent isolation and concentration via dispersive liquid-liquid microextraction(DLLME)prior to quantitative determination using high-performance liquid chromatography(HPLC).The composition and microscopic morphology of the supramolecular solvent were characterized through a series of analytical techniques,including phase diagram,Fourier transform infrared spectroscopy,scanning electron microscopy,and inverted fluorescence microscopy and so on.The density and pH value of supramolecular solvents were determined.The extraction conditions were optimized through the one-factor experiments.The experimental results demonstrated that under the optimal extraction conditions,the four kinds of sulfonamide antibiotics exhibited excellent linearity within respective detection range(R2 ≥ 0.9998)and the limits of detection(LOD)were 0.67-1.45 μg/L.Compared with literature methods,this approach offered some advantages such as simplicity of operation and less reagent consumption,and could be used for analysis and detection of sulfonamide antibiotic residues in milk samples.The present method provided technical support for food safety regulation and paved a new way for the application of supramolecular solvents in the field of extraction and separation.

Digital polymerase chain reaction(dPCR)enables absolute quantitative detection of nucleic acid samples.Since the quantitative upper and lower limits of detectable samples mainly depend on the volume and number of single droplets,the abundance of the sample to be tested,the volume of single droplets,and the number of droplets need to be adapted.For samples with unknown abundance,repeated adjustment of droplet size is not allowed.In this study,a one-step double-volume droplet generation method was proposed,and a double-volume droplet microfluidic chip was developed to verify the quantitative detection capability of the chip using a duck-derived kit.The results showed that the droplets with different volumes had different quantitative capabilities.Large-volume droplets had higher reliability for low-abundance sample concentrations,while small-volume droplets had advantages in detecting high-abundance sample concentrations.The double-volume droplets produced by the double-volume droplet microfluidic chip proposed in this study greatly improved the reliability of quantitative capabilities,and had broad application prospects in detection of precious nucleic acid samples with unknown abundance in the field of microfluidic PCR.

An electrochemical sensor based on a chitosan-carbon nanotube(CS-CNT)composite-modified glassy carbon electrode(GCE)was developed in this work for highly sensitive detection of sunset yellow(SY)in food.The CS-CNT composite dispersion was prepared via an ultrasonic dispersion method.Combined with quantum chemical calculations,the adsorption mechanism of SY molecules onto the electrode surface,facilitated by π-π conjugation and electrostatic interactions,was elucidated.The optimized experimental conditions were determined as follows:12 μL of CS-CNT dispersion modification volume,accumulation time of 300 s,and a phosphate buffer solution at pH 7.0 as supporting electrolyte solution.Experimental results demonstrated that CS significantly enhanced the dispersion of CNT,increasing the effective surface area of the modified electrode by 2.22 times(reaching 0.1587 cm2)compared to the bare GCE.The sensor exhibited a linear detection range of 3.0×10-7 mol/L to 1.0×10-5 mol/L,with a detection limit(S/N=3)of 5.0×10-10 mol/L.Satisfactory spiked recoveries ranging from 96.9%to 101.1%were achieved,along with good preparation reproducibility(relative standard deviation,RSD=4.96%).Interference tests indicated high selectivity of the sensor against citric acid,glucose,and common metal ions.The reliability of the sensor was validated through the detection of SY in actual beverage samples.This electrode design simplified operational procedures,avoiding cross-contamination between measurements,and provided an efficient solution for the on-site monitoring of food additives.

The faithful segregation of genetic material to daughter cells is a fundamental biological process and a prerequisite for autonomous construction of robustly self-replicating artificial cells.Artificial cells are mimic cell structures with part or whole functions of normal cells.The complexity of eukaryotic chromosome segregation machinery has limited its applications in the field of synthetic biology.In contrast,the plasmid segregation machineries employed by prokaryotes are relatively simple and can provide valuable approaches for the bottom-up construction of complex artificial cells.This review aimed to comprehensively analyze the origin species and working mechanism of three bacterial plasmid segregation systems,namely ParABS,ParMRC,and TubZRC systems.The current researches on plasmid segregation both in bacterial and artificial cellular systems were summarized,and the future directions of this field were also proposed.

Objective To explore the optimization strategy of Qishen Granules in treating coronary heart disease with heart failure(CHD-HF)based on data mining and the pathogenic"toxin"theory,and to predict its active components and mechanisms using network pharmacology.Methods Literature on traditional Chinese medicine(TCM)for treating CHD-HF was collected from relevant databases,and prescriptions were screened and established into a database according to inclusion and exclusion criteria.Frequency,association rules,and hierarchical clustering analyses were performed using the Ancient and Modern Medical Case Cloud Platform.Network pharmacology techniques were applied to screen potential targets of the optimized combination for treating CHD-HF,and carry out the targets and pathways enrichment analysis.Results A total of 336 articles and 339 prescriptions involving 191 herbs were included,with 12 herbs used more than 100 times.The core drug combinations for treating CHD-HF included Astragali Radix,Poria,Salviae Miltiorrhizae Radix et Rhizoma,Glycyrrhizae Radix et Rhizoma,Chuanxiong Rhizoma,etc,while commonly used detoxifying herbs included Leonuri Herb,Coptidis Rhizoma,etc.Association rule analysis yielded 10 two-item associations and 17 three-item associations;clustering analysis grouped the data into 5 categories.Based on data mining and the pathogenic"toxin"theory,the combination for treating CHD-HF was optimized to include Astragali Radix,Salviae Miltiorrhizae Radix et Rhizoma,Aconiti Lateralis Radix Praeparata,Glycyrrhizae Radix et Rhizoma,Coptidis Rhizoma,and Taraxaci Herba.Network pharmacology analysis identified 366 common targets between the optimized combination and CHD-HF,with 16 core targets screened out.Kyoto Encyclopedia of Genes and Genomes(KEGG)analysis revealed significant enrichment in pathways such as cancer pathways,lipid and atherosclerosis,Rap1 signaling pathway,hypoxia-inducible factor 1(HIF-1)signaling pathway,phosphatidylinositol-3-kinase/protein kinase B(PI3K/Akt)signaling pathway,Ras signaling pathway,and mitogen-activated protein kinase(MAPK)signaling pathway.Conclusion TCM treatment for CHD-HF primarily focuses on replenishing qi and warming yang,activating blood circulation and resolving fluid retention.Based on data mining results and the pathogenic"toxin"theory,the formulation strategy of Qishen Granules for treating CHD-HF was optimized,potentially exerting therapeutic effects through anti-inflammatory,anti-apoptotic,and anti-hypoxia physiological processes.

BACKGROUND: Spicy food consumption has been reported to be inversely associated with mortality from multiple diseases. However, the effect of spicy food intake on the incidence of vascular diseases in the Chinese population remains unclear. This study was conducted to explore this association. METHODS: This study was performed using the large-scale China Kadoorie Biobank (CKB) prospective cohort of 486,335 participants. The primary outcomes were vascular disease, ischemic heart disease (IHD), major coronary events (MCEs), cerebrovascular disease, stroke, and non-stroke cerebrovascular disease. A Cox proportional hazards regression model was used to assess the association between spicy food consumption and incident vascular diseases. Subgroup analysis was also performed to evaluate the heterogeneity of the association between spicy food consumption and the risk of vascular disease stratified by several basic characteristics. In addition, the joint effects of spicy food consumption and the healthy lifestyle score on the risk of vascular disease were also evaluated, and sensitivity analyses were performed to assess the reliability of the association results. RESULTS: During a median follow-up time of 12.1 years, a total of 136,125 patients with vascular disease, 46,689 patients with IHD, 10,097 patients with MCEs, 80,114 patients with cerebrovascular disease, 56,726 patients with stroke, and 40,098 patients with non-stroke cerebrovascular disease were identified. Participants who consumed spicy food 1-2 days/week (hazard ratio [HR] = 0.95, 95% confidence interval [95% CI] = [0.93, 0.97], P <0.001), 3-5 days/week (HR = 0.96, 95% CI = [0.94, 0.99], P = 0.003), and 6-7 days/week (HR = 0.97, 95% CI = [0.95, 0.99], P = 0.002) had a significantly lower risk of vascular disease than those who consumed spicy food less than once a week ( Ptrend <0.001), especially in those who were younger and living in rural areas. Notably, the disease-based subgroup analysis indicated that the inverse associations remained in IHD ( Ptrend = 0.011) and MCEs ( Ptrend = 0.002) risk. Intriguingly, there was an interaction effect between spicy food consumption and the healthy lifestyle score on the risk of IHD ( Pinteraction = 0.037). CONCLUSIONS Our findings support an inverse association between spicy food consumption and vascular disease in the Chinese population, which may provide additional dietary guidance for the prevention of vascular diseases.
Humans ; Male ; Female ; Prospective Studies ; Middle Aged ; Aged ; Vascular Diseases/etiology* ; Risk Factors ; China/epidemiology* ; Adult ; Proportional Hazards Models ; Cerebrovascular Disorders/epidemiology* ; East Asian People

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male