To investigate the antituberculosis activity and mechanism of myricetin from the perspective of inhibiting bacterial RNA polymerase (RNAP).

The Escherichia coli RNAP (EcoRNAP) and Mycobacterium tuberculosis RNAP (MtbRNAP) were selected as target proteins. Bacterial RNAP inhibitors were identified using in vitro transcription experiments. The activity verification of myricetin was conducted in groups A and B, with four concentration gradients for each group. In the group A, myricetin at concentrations of 0, 12.5, 25, and 50 μmol/L was added first, followed by 20 nmol/L promoter DNA; the group B first added 20 nmol/L promoter DNA, followed by myricetin at concentrations of 0, 12.5, 25, and 50 μmol/L. The inhibition mechanism was studied using electrophoretic mobility shift assay (EMSA) in two groups: the control group (samples without myricetin) and the experimental group (samples with myricetin). Finally, the antituberculosis activity was tested against both antibiotic sensitive and resistant Mycobacterium tuberculosis strains.

In vitro transcription experiments demonstrated that myricetin had inhibitory activity against both EcoRNAP (F = 13.290, P = 0.015) and MtbRNAP (F = 9.431, P = 0.028). EMSA indicated that myricetin disrupted RNAP-promoter DNA interactions during transcription initiation, especially EcoRNAP (t = 22.692, P < 0.001) and MtbRNAP (t = 21.581, P < 0.001). Drug sensitivity experiments confirmed that myricetin had antimicrobial activity against both antibiotic sensitive and resistant Mycobacterium tuberculosis strains.

Myricetin inhibits bacterial transcription by disrupting RNAP-promoter DNA interactions and has antimicrobial activity against rifampin and isoniazid resistant Mycobacterium tuberculosis. Myricetin may serve as a novel antituberculosis lead compound.

To investigate risk factors associated with increased intracranial pressure (ICP) in children with sepsis-associated encephalopathy (SAE), and to construct a risk-predicting nomogram.

This single-center prospective observational study included 154 pediatric patients with SAE admitted to the pediatric intensive care unit (PICU) of Chengdu Women's and Children's Central Hospital from May 2022 to June 2024. The cohort comprised 56 patients with elevated ICP and 98 patients without elevated ICP. Clinical characteristics and noninvasive multimodality brain monitoring indices—including the disturbance coefficient (DC), systolic velocity of middle cerebral artery (VsMCA), mean velocity of middle cerebral artery (VmMCA), diastolic velocity of middle cerebral artery (VdMCA), pulsatility index (PI), and regional cerebral oxygen saturation (rScO₂)—were compared among patients. Univariate and multivariate logistic regression analyses were used to identify independent predictors of increased ICP. Then a nomogram was developed using R software. Model performance was evaluated by the receiver operating characteristic curve and area under the curve (AUC). Internal validation was performed via bootstrap resampling.

Multivariate logistic regression analysis identified three independent risk factors for elevated ICP: lower Glasgow coma scale (GCS) score at PICU admission [odds ratio (OR) = 0.560, 95% confidence interval (CI) (0.382, 0.837), P = 0.009], elevated VsMCA on the first day [OR = 1.053, 95%CI (1.010, 1.098), P = 0.025], and elevated rScO₂ on the first day [OR = 1.199, 95%CI (1.063, 1.348), P = 0.004]. The nomogram achieved an AUC of 0.927 [95%CI (0.887, 0.967), P < 0.001], a sensitivity of 92.9%, and a specificity of 79.6%. Calibration curves showed excellent agreement between predictions and observations.

The GCS-VsMCA-rScO₂-based nomogram provides accurate and clinically feasible prediction of elevated ICP in pediatric SAE, thus facilitating early intervention.

To classify sepsis patients based on blood urea nitrogen (BUN) trajectories and to examine their association with 28-day mortality.

Based on BUN measurements taken on the 1st, 3rd, and 7th days after admission, we employed a latent growth mixture modeling (LGMM) to identify trajectory classes. Additionally, we plotted Kaplan-Meier survival curves and performed log-rank tests, followed by the application of multivariable Cox proportional hazards models to evaluate associations with 28-day mortality. Prespecified subgroup analyses were also conducted.

A total of 210 patients diagnosed with sepsis were included in this study. Based on the longitudinal trajectories of BUN, three distinct trajectory patterns were identified: a low-initial slow-decline trajectory, a high-initial persistently high-level trajectory, and a moderate-initial slow-decline trajectory. The corresponding 28-day all-cause mortality rates for these trajectories were 20.0% (25/125), 64.0% (16/25), and 46.7% (28/60), respectively. Kaplan-Meier survival analysis demonstrated clear separation of the 28-day survival curves among the three groups, with a statistically significant difference observed between groups (log-rank χ² = 20.030, P < 0.001). In comparison to the low-initial slow-decline trajectory, patients in both the high-initial persistently high-level trajectory and the moderate-initial slow-decline trajectory demonstrated significantly lower overall survival probabilities; notably, the high-initial persistently high-level group exhibited the lowest 28-day survival rate, indicating the poorest 28-day prognosis (all P < 0.001). Cox regression analysis showed that, using the low-initial slow-decline trajectory as the reference, patients classified in the high-initial persistently high-level trajectory [hazard ratio (HR) = 2.500, 95% confidence interval (CI) (1.200, 5.400), P = 0.020] and those in the moderate-initial slow-decline trajectory [HR = 2.600, 95%CI (1.400, 4.700), P = 0.002] exhibited a significantly increased risk of 28-day all-cause mortality.

Dynamic BUN trajectories delineate prognostically heterogeneous subtypes of sepsis, with the persistently high trajectory exhibiting the highest mortality rate. Continuous monitoring of BUN levels can facilitate early risk assessment and enable risk-stratified management strategies.

To investigate the relationship between the urinary complement component 3a (C3a) and the risk of acute kidney injury (AKI) and 90-day mortality in critically ill patients, and its potential predictive significance.

The prospective study included 221 patients with critical illness admitted to the ICU of Baoji People's Hospital from March 2020 to December 2022. Enzyme-linked immunosorbent assay was used to detect the urinary C3a level of patients at admission. The primary endpoint was the incidence of AKI within 48 hours after admission to the ICU. According to whether AKI occurred, all critically ill patients were divided into an AKI group and a non AKI group. The secondary endpoints included all-cause mortality at ICU and 90 days, dialysis dependence at discharge, ICU length of stay, and total length of stay.

The median urinary C3a level in the AKI group was significantly higher than that in the non AKI group [7.73 (6.02, 10.14) μg/L vs. 3.68 (2.72, 5.32) μg/L, Z = 7.199, P < 0.001]. The higher urinary C3a level was an independent influencing factor for the occurrence of AKI in critically ill patients [odds ratio = 1.083, 95% confidence interval (CI) (1.014, 0.155), P = 0.017]; the area under the receiver operating characteristic curve for predicting AKI was 0.791 [95%CI (0.729, 0.852), P < 0.001], the optimal cutoff value was 6.06 μg/L, and the sensitivity and specificity were 75.31% and 80.00% respectively. In terms of short-term prognosis analysis, the higher urinary C3a level was also an independent influencing factor for the 90-day mortality in critically ill adult patients [hazard ratio = 1.046, 95%CI (1.023, 1.069), P < 0.001]. Patients were divided into a low-level urine C3a group (≤ 5.28 μg/L, 110 cases) and a high-level urine C3a group (> 5.28 μg/L, 111 cases) based on the median value. Compared with patients with low urinary C3a levels, patients with high urinary C3a levels had a lower 90-day survival rate (log rank χ² = 50.668, P < 0.001). In addition, compared with patients with low urinary C3a levels, patients with high urinary C3a levels had a higher ICU mortality rate [10.91% (12/110) vs. 47.75% (53/111), χ² = 36.110, P < 0.001], a higher proportion of dialysis dependence [2.73% (3/110) vs. 9.91% (11/111), χ² = 4.804, P = 0.028], longer ICU duration [8.00 (5.00, 14.00) d vs. 18.00 (12.75, 38.00) d, Z = 2.587, P = 0.010], and longer total hospital duration [10.00 (6.00, 18.00) d vs. 24.50 (17.00, 44.00) d, Z = 2.647, P = 0.008].

The higher urinary C3a levels at admission are associated with an increased risk of AKI and 90-day mortality, and have the potential to serve as a predictive biomarker for AKI and 90-day mortality risk in critically ill patients.

With the evolving spectrum of cardiovascular diseases and changing characteristics of patient populations, the traditional coronary care unit can no longer meet the demands of critically ill patients. In recent years, the development of cardiac intensive care unit (CICU) has become a central focus in the field of critical cardiology. This expert consensus, initiated by the Heart Critical Care Subdivision of Zhejiang Medical Data Industry Research Association and the Cardiac Critical Care Committee of Chinese Medical Doctor Association, was jointly drafted by specialists from multiple tertiary hospitals with extensive experience in cardiac critical care. Drawing upon comprehensive reviews of international and domestic guidelines, available evidence, and clinical practice, the consensus outlines recommendations on CICU models of care, tiered management systems, ward design, equipment allocation, staffing, and training frameworks. The consensus aims to provide practical and evidence-based guidance for CICU establishment and management in China, foster standardized development nationwide, and facilitate alignment with international best practices.