Objective To evaluate the predictive value of different machine learning models constructed in a multicenter environment for potential organ donors and verify their clinical application feasibility. Methods The study included 2 000 inpatients admitted to five domestic tertiary hospitals from January 2020 to December 2023, who met the criteria for potential organ donation assessment. They were randomly divided into a training set and an internal validation set (7∶3). Another 300 similar patients admitted to the First Affiliated Hospital of Harbin Medical University from January 2024 to April 2025 were included as an external validation set. The area under the curve (AUC), sensitivity, specificity, accuracy and F1-score of three models were compared, and the consistency of the potential organ donor determination process was tested. Multivariate logistic regression analysis was used to identify predictive factors of potential organ donors. Decision curve analysis (DCA) was employed to verify the resource efficiency of each model, and the threshold interval and intervention balance point were assessed. Results Apart from age, there were no significant differences in other basic characteristics among the centers (all P>0.05). The consistency of the potential organ donor determination process among researchers in each center was good [all 95% confidence interval (CI) lower limits >0]. In the internal validation set, the XGBoost model had the best predictive performance (AUC=0.92, 95% CI 0.89-0.94) and the best calibration (P=0.441, Brier score 0.099). In the external validation set, the XGBoost model also had the best predictive performance (AUC=0.91, 95% CI 0.88-0.94), outperforming logistic regression and random forest models. Multivariate logistic regression showed that mechanical ventilation had the greatest impact (odds ratio=2.06, 95% CI 1.54-2.76, P<0.001). DCA indicated that the XGBoost model had the highest net benefit in the threshold interval of 0.2-0.6. The “treat all” strategy only had a slight advantage at extremely low thresholds. The recommended threshold interval, which balances intervention costs and clinical benefits, considers ≥50% positive predictive value (PPV) and ≤50 referrals per 100 high-risk patients. Conclusions The XGBoost model established in a multicenter environment is accurate and well-calibrated in predicting potential organ donors. Combined with DCA, it may effectively guide the timing of clinical interventions and resource allocation, providing new ideas for the assessment and management of organ donation after brain death.

Objective:To explore the early predictive value of umbilical cord blood S100β protein and lactate combined with amplitude integrated electroencephalogram（aEEG）in small for gestational age（SGA）preterm infants with brain injury.Methods:One hundred and six cases of SGA preterm infants were enrolled in this study in Neonatology Department of Inner Mongolia People's Hospital from January 2019 to December 2021. Umbilical cord blood serum S100β protein and lactate at birth of All SGA preterm infants were tested，and aEEG was monitored at 6h and 72 h after birth，corrected gestational age of 32 weeks and 37 weeks. According to the diagnostic criteria of brain injury in preterm infants，SGA preterm infants were divided into brain injury group（45 cases）and non-brain injury group（61 cases），and compared the differences of S100β protein，lactate and the designated time aEEG between the two groups.SGA preterm infants with brain injury were further divided into symmetrical group（28 cases）and non-symmetrical group（15 cases）. The differences of umbilical cord blood S100β protein and lactate level between the two groups were compared，and the diagnostic value in different types of SGA preterm infants with brain injury was also compared.Results:SGA preterm infants in the brain injury group had significantly higher levels of umbilical cord blood S100β protein［（0.826±0.218）μg/L vs（0.397±0.196）μg/L， t=8.316， P<0.05］and lactate［（8.5±1.3）mmol/L vs（3.8±0.9）mmol/L， t=3.281， P<0.05］than those in non-brain injury group.Symmetric SGA group had higher level of S100β protein than the asymmetric SGA group［（0.924±0.205）μg/L vs（0.438±0.196）μg/L， t=5.734， P<0.05］.But there was no statistically significant difference in lactate levels［（5.6±1.4）mmol/L vs（3.9±1.2）mmol/L， t=0.932， P>0.05］between symmetric SGA group and asymmetric SGA group. The abnormal rates of aEEG in brain injury group and non-brain injury group were respectively 100%（45/45）vs 22.95%（14/61）at 6 h after birth，95.56%（43/45）vs 16.39%（10/61）at 72 h after birth，62.22%（28/45）vs 6.56%（4/61）at 32 weeks of corrected gestational age，22.22%（10/45）vs 3.28%（2/61）at 37 weeks of corrected gestational age. The abnormal rate of brain injury group was higher than the non-brain injury group in the same nodal time，and the differences were statistically significant（ χ 2 value respectively 62.292，64.913，38.074，9.257，all P<0.05）. Conclusion:There were significant value in umbilical cord blood S100β protein，lactate level and aEEG monitoring in the early diagnosis in preterm infants SGA with brain injury. The combination of the three might be more helpful for the early diagnosis and timely treatment of brain injury in SGA preterm infants.

Children's sleep health runs through the entire process of children's growth and development and is of great significance.Sleep disorders are one of the important problems affecting children's grow，development and growth health.The number of pediatric patients with sleep disorders is on the rise year by year.Current studies show that the disturbance of children's sleep homeostasis is usually accompanied by the increase of neuroendocrine system activities，the activation of immune system，metabolic disorders，etc，lead to the corresponding hormones（such as cortisol），inflammatory factors，metabolic substances and other homeostasis changes，mutual influence，forming a vicious cycle.In addition，the relationship between genetic factors and sleep is also increasingly concerned.This article reviews the mechanisms，influencing factors and research progress of children's sleep health and sleep disorders，aiming to provide a reference for clinical intervention in children′s sleep problems.

BACKGROUND: Carbapenem-resistant Klebsiella pneumoniae (CRKP) is considered a serious global threat. However, little is known regarding the multidrug resistance (MDR) mechanisms of CRKP. This study investigated the phenotypes and MDR mechanisms of CRKP and identified their clonal characteristics. METHODS: PCR and sequencing were utilized to identify antibiotic resistance determinants. Integron gene cassette arrays were determined by restriction fragment length polymorphism (RFLP) analysis. Multi-locus sequence typing (MLST) and pulsed-field gel electrophoresis (PFGE) were used for epidemiological analysis. Plasmids were typed by using a PCR-based replicon typing and analyzed by conjugation and transformation assays. RESULTS: Seventy-eight strains were identified as resistant to at least one carbapenem; these CRKP strains had a high prevalence rate (38.5%, 30/78) of carbapenemase producers. Additionally, most isolates harbored MDR genes, including Extended spectrum β-lactamases (ESBLs), AmpC, and quinolone and aminoglycoside resistance genes. Loss of porin genes was observed, and Class 1 integron was detected in 66.7% of the investigated isolates. PFGE and MLST results excluded the occurrence of clonal dissemination among these isolates. CONCLUSIONS: A high prevalence of NDM-1 genes encoding carbapenem resistance determinants was demonstrated among the K. pneumoniae isolates. Importantly, this is the first report of bla(NDM-1) carriage in a K. pneumoniae ST1383 clone in China and of a MDR CRKP isolate co-harboring bla(NDM-1), bla(KPC-2), bla(CTX-M), bla(SHV), acc(6′)-Ib, rmtB, qnrB, and acc(6′)-Ib-cr.
China* ; Clone Cells ; Drug Resistance, Bacterial ; Drug Resistance, Microbial ; Drug Resistance, Multiple* ; Electrophoresis, Gel, Pulsed-Field ; Genes, MDR ; Integrons ; Klebsiella pneumoniae* ; Klebsiella* ; Molecular Epidemiology ; Phenotype ; Plasmids ; Pneumonia ; Polymerase Chain Reaction ; Polymorphism, Restriction Fragment Length ; Prevalence ; Replicon

Objective To explore the effect of NPY on activation of primary microglia and the production of in?terleukin-1β. Methods Rat primary cortical microglia was cultured and divided into control group, LPS group, NPY+LPS group, NPY group and BIBP3226+NPY+LPS group. Microglia in control group were incubated with serum-free me?dium for 6 h;microglia in LPS group were incubated with serum-free medium plus LPS for 6 h;microglia in NPY+LPS group were incubated with serum-free medium plus NPY and LPS for 6 h; microglia cells in NPY group were incubat?ed in serum-free medium plus NPY for 6 h; microglia cells in BIBP3226+NPY+LPS group were incubated in se?rum-free medium including BIBP3226 、NPY and LPS for 6 h. After 6 h , Primary cultured microglia were stained us?ing IBA-1 antibody and examined under the fluorescence microscope. The protein levels of IL-1βin the culture media and the mRNA expression levels of IL-1βin the microglia of different groups were detected using the methods of Elisa and RT-PCR. Results After 6 h, the contents of IL-1 βin the culture media and the mRNA expression levels of IL-1βin the cells of LPS group increased remarkably compared with control group (P<0.05) and the microglia were activat? ed. Compared with LPS group, the contents of IL-1 βin the culture media. the mRNA expression levels of IL-1β and the activity of microglia in LPS+NPY group were significantly decreased .Compared with LPS+NPY group, the contents of IL-1βin the culture media. the mRNA expression levels of IL-1β and the activity of microglia in BIBP3226+NPY+LPS group were increased (P<0.05). There were no significant differences in the contents of IL-1βin the culture media. the mRNA expression levels of IL-1βand the activity of microglia between BIBP3226+NPY+LPS group and LPS group or between NPY group and the control group. Conclusion NPY can inhibit the biological activity of microglia and IL-1βproduction through NPY Y1 receptorin the microglia.

Objective\ To detect thrombomodulin protein in 18 weeks human fetal lung. Methods\ SP method was used in the study. Results\ It showed that, in fetal lung tissues, thrombomodulin expressed in the endothelial cells of capillaries surrounding the primary alveoli, but it was absent in cuboid cells and ciliated\|columnary epithelium cells and cartilage. Conclusion\ Our results suggest that thrombomodulin does not exist in middle and late stage's human fetal lung.\;