Objective: To systematically evaluate the association between random urinary electrolyte levels and hypertension among children and adolescents in Guizhou Province, so as to provide evidence for region specific dietary guidance and interventions. Methods: In 2023, a total of 2 480 children and adolescents aged 6 to 17 years were recruited from a nine-year coherent style school in Guizhou Province in a children health cohort, with follow ups conducted in 2024 and 2025. Random urine samples were collected to measure urinary sodium, potassium, calcium, and chloride, and the urinary sodium to potassium ratio (Na/K) was calculated. The diagnosis of hypertension was based on the criteria established by the Chinese Guidelines for Hypertension Prevention and Treatment (2024 revised edition) and relevant research. Linear mixed models and multinomial Logistic regression were used to assess the associations of urinary electrolytes with systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), and the risk of hypertension. Results: At baseline, SBP, DBP, and MAP were 102.33 (94.33, 110.33), 61.33 (56.33, 67.00) and 75.22 (69.67, 81.33)mmHg among children and adolescents, respectively. After adjusting for potential confounders and two follow-ups, higher urinary Na/K ratio was positively associated with higher of SBP ( β=0.054, 95%CI =0.028- 0.081 ) and MAP ( β=0.038, 95%CI =0.010-0.066), as well as higher risks of hypertension ( OR=1.248, 95%CI =1.006-1.548) (all P <0.05). Higher of urinary chloride levels were positively associated with higher of SBP ( β=0.088, 95%CI = 0.009- 0.167), whereas higher of urinary potassium (SBP: β=-0.062, 95%CI =-0.096 to -0.028; MAP: β=-0.041, 95%CI = -0.078 to -0.005) and calcium levels (SBP: β=-0.036, 95%CI =-0.065 to -0.007) were negatively associated with blood pressure (all P < 0.05 ). Conclusion The urinary Na/K, as a comprehensive electrolyte marker, more stably reflects sodium load and excretory pressure in children and adolescents, and may serve as an early predictor of hypertension risk.

Objective: To construct a risk prediction model for pediatric metabolic dysfunction associated steatotic liver disease (MASLD), so as to provide practical tool for the early identification of high risk children. Methods: A healthy cohort of children in Southwest China was established from January 2021 to April 2025. A nested case-control study design was used to include 507 cases MASLD group and 507 cases in non MASLD group. Data on physical measurements, blood biochemical parameters, and liver ultrasound indicators were collected. Conditional Logistic regression was used to analyze the relationship between individual variables and MASLD, Lasso regression was applied for multivariable screening, and a high risk prediction model was constructed and presented in the form of a nomogram. Internal validation was performed using 10 repeated ten fold cross validations to assess model discrimination, accuracy, sensitivity, and specificity. Results: Logistic regression analysis showed that MASLD was associated with central obesity ( OR=22.11, 95%CI =15.62-31.29), apolipoprotein B ( OR=30.24, 95%CI =12.42-73.63), increased hepatorenal echo ( OR=326.00, 95%CI =183.87-578.01), hepatomegaly ( OR=24.98, 95%CI =16.66-37.46) (all P <0.05). The Lasso regression jointly selected 6 key variables, including hepatorenal echo, central obesity, hepatomegaly, right liver lobe inclination, body mass index, and alanine amino transferase. The results of cross validation showed that the average area under the curve (AUC) was 0.999 5, the average accuracy was 98.74%, and the sensitivity and specificity were 98.21% and 99.22% respectively, indicating a good predictive effect of the model. Conclusion The risk prediction model for high risk MASLD among children based on ultrasound and clinical indicators has good prediction effect, which is helpful for the early identification and risk stratification of pediatric MASLD.

Objective To evaluate the effect of donor gender on short-term survival rate of lung transplant recipients. Methods A retrospective analysis was conducted on the data of 1 066 lung transplant recipients. The log-rank test was used to evaluate the differences in short-term fatality among different donor gender groups and donor-recipient gender combination groups. Multivariate Cox regression, propensity score (PS) regression, and propensity score matching (PSM) were employed to control for confounding factors and further assess the differences in fatality. Subgroup analyses were also performed based on donor gender. Results Multivariate Cox regression analysis showed no statistically significant differences in fatality at 30 days, 1 year, 2 years and 3 years postoperatively between male and female donor groups (all P>0.05). After PS regression and PSM, univariate Cox regression analysis indicated that recipients from female donors had a higher fatality at 2 years postoperatively compared to those from male donors, with hazard ratios (95% confidence intervals) of 1.29 (1.01-1.65) and 1.36 (1.03-1.80) respectively. Multivariate Cox regression analysis also revealed no statistically significant differences in fatality at various follow-up time points among different donor-recipient gender combination groups (all P>0.05). Subgroup analyses based on donor sex showed no statistically significant differences in fatality among recipients of different gender within either male or female donor groups (all P>0.05). Conclusions Female donors may reduce the short-term postoperative survival rate of lung transplant recipients, but this negative impact is not sustainable in the long term. At present, there is no evidence to support the inclusion of sex as a factor in lung allocation rules.

Lung cancer is the most prevalent malignant tumor worldwide. For lung cancer patients with multiple intrapulmonary metastases or impaired lung function, complete tumor resection is challenging, and the prognosis is poor. Lung transplantation demonstrates potential therapeutic value in achieving complete tumor resection, improving lung function, and enhancing quality of life. Advances in tumor detection technologies such as positron emission tomography-computed tomography and circulating tumor DNA, along with the development of comprehensive treatment strategies for lung cancer, provide powerful tools for accurately predicting tumor recurrence and treatment outcomes following lung transplantation. The feasibility of lung transplantation as a treatment for lung cancer is receiving increasing attention. This article reviews the history and clinical management of lung transplantation for lung cancer.

Enhanced recovery after surgery (ERAS) is a series of perioperative optimization measures based on evidence-based medicine aimed at achieving rapid recovery. Existing studies have shown that ERAS can effectively reduce surgical stress, decrease the incidence of complications, shorten hospital stays, save medical costs, and improve patient satisfaction. Although lung transplantation techniques have become increasingly mature, lung transplant recipients still have a high incidence of complications during perioperative period. To further improve the perioperative survival rate of lung transplant recipients, introducing ERAS concept into the perioperative management strategy of lung transplantation is of great significance for reducing incidence of perioperative complications, promoting rapid recovery and long-term survival of lung transplant recipients. This article discusses the advances in application of ERAS concept in the perioperative management of lung transplantation, aiming to provide references for optimizing the perioperative management of lung transplant recipients and reducing perioperative complications.

HDAC7, a member of class IIa HDACs, plays a pivotal regulatory role in tumor, immune, fibrosis, and angiogenesis, rendering it a potential therapeutic target. Nevertheless, due to the high similarity in the enzyme active sites of class IIa HDACs, inhibitors encounter challenges in discerning differences among them. Furthermore, the substitution of key residue in the active pocket of class IIa HDACs renders them pseudo-enzymes, leading to a limited impact of enzymatic inhibitors on their function. In this study, proteolysis targeting chimera (PROTAC) technology was employed to develop HDAC7 drugs. We developed an exceedingly selective HDAC7 PROTAC degrader B14 which showcased superior inhibitory effects on cell proliferation compared to TMP269 in various diffuse large B cell lymphoma (DLBCL) and acute myeloid leukemia (AML) cells. Subsequent investigations unveiled that B14 disrupts BCL6 forming a transcriptional inhibition complex by degrading HDAC7, thereby exerting proliferative inhibition in DLBCL. Our study broadened the understanding of the non-enzymatic functions of HDAC7 and underscored the importance of HDAC7 in the treatment of hematologic malignancies, particularly in DLBCL and AML.

OBJECTIVES: To explore the effect of A. muciniphila gavage on intestinal microbiota and gut-brain interaction disorders (DGBIs) in gp120tg transgenic mouse models of HIV-associated neurocognitive disorder (HAND). METHODS: Intestinal microbiota was detected by 16S rRNA gene sequencing in 6-, 9-, and 12-month-old wild-type (WT) mice and gp120tg transgenic mice. The 12-month-old WT and transgenic mice were divided into 2 groups for daily treatment with PBS or A.muciniphila gavage (2×10⁸ CFU/mouse) for 6 weeks. After the treatment, immunohistochemistry, ELISA and qPCR were used to detect changes in colonic expression levels of glycosylated mucins, MBP and IL-1β, eosinophil infiltration, serum lipopolysaccharide (LPS) levels, and colonic expressions of occludin, ZO-1, IL-10, TNF-α and INF-γ mRNA. Morris water maze test and immunofluorescence assay were used to assess learning and spatial memory abilities and neuronal damage of the mice. RESULTS: Compared with WT mice, the transgenic mice exhibited significantly lowered Simpson's diversity of the intestinal microbiota with reduced abundance of Akkermansia genus, increased serum LPS levels and decreased colonic expression of glycosylated mucin. A.muciniphila gavage obviously ameliorated the reduction of glycosylated mucin in the transgenic mice without causing significant changes in body weight. The 12-month-old gp120tg mice had significantly decreased cdonic expressions of Occludin and ZO-1 with increased eosinophil infiltration and TNF-β, INF-γ and IL-1β levels and obviously lowered IL-10 level; all these changes were significantly mitigated by A.muciniphila gavage, which also improved cognitive impairment and neuronal loss in the hippocampus and cortex of the transgenic mice. CONCLUSIONS The gp120tg mice have lower intestinal microbiota richness and diversity than WT mice. The 12-month-old gp120tg mice have significantly reduced Akkermansia abundance with distinct DGBIs-related indexes, and A. muciniphila gavage can reduce intestinal barrier injury, colonic inflammation and eosinophil activation, cognitive impairment and brain neuron injury in these mice.
Animals ; Mice, Transgenic ; Gastrointestinal Microbiome ; Mice ; Brain ; HIV Envelope Protein gp120/genetics* ; Akkermansia ; Disease Models, Animal

Psoriasis is a chronic inflammatory skin disease, and its pathogenesis is largely modulated by abnormal angiogenesis. Previous research has indicated that AlkB homolog 5 (ALKBH5), an important demethylase affecting N⁶-methyladenosine (m⁶A) modification, plays a role in regulating angiogenesis in cardiovascular and eye diseases. Our present study found that ALKBH5 was upregulated and co-localized with cluster of differentiation 31 (CD31) in the skin of IMQ group compared with control group. ALKBH5-deficient mice decreased IMQ-induced psoriatic dermatitis and exhibited histological improvements, including decreased epidermal thickness, hyperkeratosis, numbers of dermal capillary vessels and inflammatory cell infiltration. ALKBH5-KO mice alleviated angiogenesis in psoriatic lesions by downregulating the protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway. Additionally, the expression of ALKBH5 was significantly upregulated in IL-17A-induced human umbilical vein endothelial cells (HUVECs), which further promoted the expression of angiogenesis-related cytokines and endothelial cell proliferation. Cell proliferation and angiogenesis were suppressed in ALKBH5 knockdown group, whereas ALKBH5 overexpression promoted these processes. The regulation of angiogenesis in HUVECs by ALKBH5 was facilitated through the AKT-mTOR pathway. Collectively, ALKBH5 plays a pivotal role in psoriatic dermatitis and angiogenesis, which may offer a new potential targets for treating psoriasis.
Animals ; Psoriasis/chemically induced* ; Mice ; Humans ; Neovascularization, Pathologic/genetics* ; Human Umbilical Vein Endothelial Cells/metabolism* ; AlkB Homolog 5, RNA Demethylase/genetics* ; Proto-Oncogene Proteins c-akt/metabolism* ; TOR Serine-Threonine Kinases/metabolism* ; Cell Proliferation ; Mice, Knockout ; Disease Models, Animal ; Signal Transduction ; Male ; Skin/blood supply* ; Mice, Inbred C57BL ; Angiogenesis

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.