Objective:To construct a predictive model for postoperative delirium (POD) in patients undergoing gastrointestinal surgery using machine learning.Methods:This retrospective study used clinical data from patients who underwent gastrointestinal surgery at Subei People′s Hospital between September 2022 and April 2024. The entire dataset was randomly divided into the training and validation sets in an 8∶2 ratio. Multivariate logistic regression analysis was conducted to identify the factors influencing POD. Eleven machine learning models were established and compared. The performance of the models was validated using metrics, including accuracy, precision, recall, Youden′s index, F1 score, Matthews′ correlation coefficient, Kappa coefficient, log loss, and Brier score. Receiver operating characteristic and calibration curves were plotted to assess the discrimination and consistency of the model. Shapley additive explanations were used in Python for interpretative analysis of the model with the best predictive performance, and the importance of the feature parameters was ranked.Results:A total of 1, 785 patients were ultimately included, of which 833 (46.67%) experienced POD. The results of multivariate logistic regression analysis revealed that advanced age, lower preoperative serum calcium ion concentration, postoperative pulmonary infection, and higher preoperative systolic blood pressure were independent risk factors for POD in patients undergoing gastrointestinal surgery, while laparoscopic surgery was a protective factor ( P<0.05). Among the 11 machine learning models, the categorical feature gradient boosting model exhibited the best performance, with an area under the receiver operating characteristic curve of 0.82 (95% confidence interval 0.77-0.87). The ranking of feature importance indicated that age had the greatest contribution in predicting POD. Conclusions:The predictive model for POD established based on the categorical boosting algorithm has higher predictive efficacy and clinical application value in patients undergoing gastrointestinal surgery.

Objective To investigate the effect of T2-fluid attenuated inversion recovery(T2-FLAIR)sequence on the appearance of ivy sign in patients with moyamoya disease under different imaging conditions.Methods Coronal T2-FLAIR scans were performed in 51 consecutive adult patients with moyamoya disease who had not undergone surgery and had their first visit to this hospital between March and July of 2024.According to the scanning conditions,the patients were divided into 19 and 14 of the echo train length in two groups,and 103,144,and 195 ms of the time of echo(TE)in three groups,respectively.The left and right cerebral hemispheres and whole brains were scored according to the cerebral vascular anatomy,and scores of the ivy sign of left and right cerebral hemispheres and whole brain were compared.Results There was no statistical significance in the ivy sign scores of right and left cerebral hemispheres and whole brain between the two groups with 19 and 14 of the echo train length(P＞0.05).Comparison of ivy sign scores in right and left cerebral hemispheres and whole brain was statistically significant among the three groups of TE at 144,103 and 195 ms(P＜0.05).Conclusion The best appearance of ivy sign in patients with moyamoya disease is seen under the condition of TE at 195 ms,so appropriately extending the TE time is helpful for ivy sign display.

Benzylisoquinoline alkaloids (BIAs) are a structurally diverse group of plant metabolites renowned for their pharmacological properties. However, sustainable sources for these compounds remain limited. Consequently, researchers are focusing on elucidating BIA biosynthetic pathways and genes to explore alternative sources using synthetic biology approaches. CYP80B, a family of cytochrome P450 (CYP450) enzymes, plays a crucial role in BIA biosynthesis. Previously reported CYP80Bs are known to catalyze the 3'-hydroxylation of (S)-N-methylcoclaurine, with the N-methyl group essential for catalytic activity. In this study, we successfully cloned a full-length CYP80B gene (StCYP80B) from Stephania tetrandra (S. tetrandra) and identified its function using a yeast heterologous expression system. Both in vivo yeast feeding and in vitro enzyme analysis demonstrated that StCYP80B could catalyze N-methylcoclaurine and coclaurine into their respective 3'-hydroxylated products. Notably, StCYP80B exhibited an expanded substrate selectivity compared to previously reported wild-type CYP80Bs, as it did not require an N-methyl group for hydroxylase activity. Furthermore, StCYP80B displayed a clear preference for the (S)-configuration. Co-expression of StCYP80B with the CYP450 reductases (CPRs, StCPR1, and StCPR2), also cloned from S. tetrandra, significantly enhanced the catalytic activity towards (S)-coclaurine. Site-directed mutagenesis of StCYP80B revealed that the residue H205 is crucial for coclaurine catalysis. Additionally, StCYP80B exhibited tissue-specific expression in plants. This study provides new genetic resources for the biosynthesis of BIAs and further elucidates their synthetic pathway in natural plant systems.
Cytochrome P-450 Enzyme System/chemistry* ; Benzylisoquinolines/chemistry* ; Hydroxylation ; Plant Proteins/chemistry* ; Alkaloids/metabolism* ; Stephania tetrandra/genetics*

Homo- or heterodimeric compounds that affect dimeric protein function through interaction between monomeric moieties and protein subunits can serve as valuable sources of potent and selective drug candidates. Here, we screened an in-house dimeric natural product collection, and panepocyclinol A (PecA) emerged as a selective and potent STAT3 inhibitor with profound anti-tumor efficacy. Through cross-linking C712/C718 residues in separate STAT3 monomers with two distinct Michael receptors, PecA inhibits STAT3 DNA binding affinity and transcription activity. Molecular dynamics simulation reveals the key conformation changes of STAT3 dimers upon the di-covalent binding with PecA that abolishes its DNA interactions. Furthermore, PecA exhibits high efficacy against anaplastic large T cell lymphoma in vitro and in vivo, especially those with constitutively activated STAT3 or STAT3^Y640F. In summary, our study describes a distinct and effective di-covalent modification for the dimeric compound PecA to disrupt STAT3 function.

The prefrontal cortex (PFC) plays a pivotal role in orchestrating higher-order emotional and cognitive processes, a function that depends on the precise modulation of synaptic activity. Although pharmacological studies have demonstrated that dopamine signaling through dopamine D1 receptor (DRD1) in the PFC is essential for these functions, the cell-type-specific and molecular mechanisms underlying the neuromodulatory effects remain elusive. Using cell-type-specific knockout mice and patch-clamp recordings, we investigated the regulatory role of DRD1 on neurons and astrocytes in synaptic transmission and plasticity. Furthermore, we explored the mechanisms by which DRD1 on astrocytes regulate synaptic transmission and plasticity at the cellular level, as well as emotional and cognitive functions at the behavioral level, through two-photon imaging, microdialysis, high-performance liquid chromatography, transcriptome sequencing, and behavioral testing. We found that conditional knockout of the Drd1 in astrocytes (CKO^AST) increased glutamatergic synaptic transmission and long-term potentiation (LTP) in the medial prefrontal cortex (mPFC), whereas Drd1 deletion in pyramidal neurons did not affect synaptic transmission. The elevated level of d-serine in the mPFC of CKO^AST mice increased glutamatergic transmission and LTP through NMDA receptors. In addition, CKO^AST mice exhibited abnormal emotional and cognitive function. Notably, these behavioral changes in CKO^AST mice could be reversed through the administration of d-serine degrease to the mPFC. These results highlight the critical role of the astrocytic DRD1 in modulating mPFC synaptic transmission and plasticity, as well as higher brain functions through d-serine, and may shed light on the treatment of mental disorders.

Objective:To construct a predictive model for postoperative delirium (POD) in patients undergoing gastrointestinal surgery using machine learning.Methods:This retrospective study used clinical data from patients who underwent gastrointestinal surgery at Subei People′s Hospital between September 2022 and April 2024. The entire dataset was randomly divided into the training and validation sets in an 8∶2 ratio. Multivariate logistic regression analysis was conducted to identify the factors influencing POD. Eleven machine learning models were established and compared. The performance of the models was validated using metrics, including accuracy, precision, recall, Youden′s index, F1 score, Matthews′ correlation coefficient, Kappa coefficient, log loss, and Brier score. Receiver operating characteristic and calibration curves were plotted to assess the discrimination and consistency of the model. Shapley additive explanations were used in Python for interpretative analysis of the model with the best predictive performance, and the importance of the feature parameters was ranked.Results:A total of 1, 785 patients were ultimately included, of which 833 (46.67%) experienced POD. The results of multivariate logistic regression analysis revealed that advanced age, lower preoperative serum calcium ion concentration, postoperative pulmonary infection, and higher preoperative systolic blood pressure were independent risk factors for POD in patients undergoing gastrointestinal surgery, while laparoscopic surgery was a protective factor ( P<0.05). Among the 11 machine learning models, the categorical feature gradient boosting model exhibited the best performance, with an area under the receiver operating characteristic curve of 0.82 (95% confidence interval 0.77-0.87). The ranking of feature importance indicated that age had the greatest contribution in predicting POD. Conclusions:The predictive model for POD established based on the categorical boosting algorithm has higher predictive efficacy and clinical application value in patients undergoing gastrointestinal surgery.

Objective:To analyze the clinical and genetic characteristics of children diagnosed with Noonan-syndrome associated with loose anagen hair (NS-LAH).Methods:A retrospective analysis was conducted on the clinical data of 5 children diagnosed with NS-LAH by the Endocrinology Department of the Capital Institute of Pediatrics from January 2018 to June 2024. This analysis encompassed the patients′ demographic information, clinical manifestations, distinguishing features, treatment regimens, and prognostic outcomes to elucidate their clinical characteristics. Additionally, whole-exome sequencing and Sanger sequencing were utilized to investigate the genetic etiology within the families, and the identified variations were interpreted according to the guidelines of the American College of Medical Genetics and Genomics.Results:Among the 5 NS-LAH patients, there were 3 boys and 2 girls, with ages at diagnosis ranging from 2.3 to 7.7 years old. All patients presented with short stature as a primary complaint. Birth histories were generally unremarkable, though case 2 and 5 of macrosomia were noted. In addition to the characteristic facial features of Noonan syndrome, short stature, and varying degrees of intellectual and motor developmental delay, all 5 patients exhibited sparse hair that was easily shed, as well as enlarged head circumferences. Four patients showed structural cardiac abnormalities, which included a case of hypertrophic cardiomyopathy, 2 cases of atrial septal defect, and 1 case of patent foramen ovale. Genetic analysis revealed heterozygous missense variantion in SHOC2 gene in 4 patients, comprising 3 cases with c.4A>G (p.S2G) and one case with c.519G>C (p.M173I). Additionally, one patient was found to have a heterozygous missense variantion c.146C>G (p.P49R) in PPP1CB gene. Three children were diagnosed with growth hormone deficiency and treated with growth hormone for 1.7, 2.7 and 0.5 years. This resulted in significant improvements in height, with annual increases of 11.8, 8.4 and 13.0 cm, respectively. Among the 4 patients with SHOC2 variantions, 2 developed systemic lupus erythematosus and 1 exhibited symptoms of arthritis.Conclusions:Growth failure is the primary complaint in patients with NS-LAH. Key characteristic findings include enlarged head circumference and sparse, loose hair. Growth hormone deficiency is commonly associated with NS-LAH, and growth hormone therapy is generally effective. Furthermore, patients carrying the classic variantion in SHOC2 (c.4A>G) may have an increased risk of developing autoimmune diseases.

Objective:To investigate the risk factors and construct a nomogram prediction model for neonatal bacterial meningitis (BM).Methods:A retrospective cohort study was conducted on 1 228 neonates who underwent lumbar puncture for cerebrospinal fluid examination in the Department of Neonatology at Gansu Provincial Women and Child Healthcare Hospital from December 2019 to February 2024. The subjects were randomly divided into a training cohort and a validation cohort at a ratio of 7∶3 using a computer program. Rank sum test or Chi-square tests were used to compare differences between the two cohorts. The subjects were divided into BM and non-BM groups based on the presence or absence of BM. Multivariate logistic regression analysis (forward stepwise regression method) was used in the training cohort to identify risk factors for BM. The area under the receiver operating characteristic curve (AUC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess the discrimination and calibration of the model, respectively. Calibration curves were used to evaluate the accuracy of the model and to construct the nomogram. Internal validation was performed using the Bootstrap resampling method. Decision curve analysis was used to assess the clinical utility of the model. Results:Among the 1 228 neonates, 151 (12.3%) had BM. The training cohort included 859 neonates, of whom 106 (12.3%) had BM and 753 (87.7%) did not. The validation cohort included 369 neonates, of whom 45 (12.2%) had BM and 324 (87.8%) did not. The results of the multivariate logistic regression analysis in the training cohort showed that sepsis ( OR=4.446, 95% CI:2.583-7.653), convulsions ( OR=3.749, 95% CI:1.930-7.280), high maximum body temperature ( OR=2.027, 95% CI:1.636-2.513), and elevated C-reactive protein ( OR=1.007, 95% CI:1.003-1.012) were independent risk factors for BM, while greater gestational age at birth ( OR=0.946, 95% CI: 0.898-0.995) and higher hemoglobin levels ( OR=0.990, 95% CI:0.981-0.998) were protective factors for BM (all P<0.05). Based on these findings, a nomogram prediction model for neonatal BM was constructed and validated for accuracy. The AUC values of the nomogram model in the training and validation cohorts were 0.796 (95% CI: 0.750-0.843) and 0.781 (95% CI: 0.700-0.862), respectively. The Hosmer-Lemeshow goodness-of-fit test showed P>0.05 in both cohorts. The clinical decision curve analysis demonstrated good net benefit across most threshold ranges. Conclusions:Sepsis, convulsions, high maximum body temperature, and elevated C-reactive protein increase the risk of neonatal BM. The nomogram model constructed based on these factors, combined with gestational age and hemoglobin levels, provides a reference value for predicting the risk of neonatal BM.

Objective:To analyze the accuracy of nine estimation methods for umbilical venous catheterization (UVC) insertion depth in neonates.Methods:This prospective study enrolled neonates who underwent successful UVC placement in the Department of Neonatology at Gansu Provincial Women and Child Healthcare Hospital between September 2023 and October 2024. The standard catheter tip position was defined as the junction of the inferior vena cava and right atrium, with a deviation of ≤0.5 cm considered accurate. Patients were stratified by birth weight (BW) into three groups: <1 500 g, 1 500- 2 499 g, and ≥2 500 g. The actual UVC depth was compared with depths estimated using nine methods: Shukla formula, modified Shukla formula, JSS formula, BW formula, Tambasco formula, modified Tambasco formula, Dunn's nomogram, body surface measurement, and ultrasonographic measurement. Accuracy was evaluated using nonparametric tests and Bland-Altman agreement analysis.Results:The study included 111 neonates: 41 (36.9%) in the <1 500 g group, 55 (49.6%) in the 1 500-2 499 g group, and 15 (13.5%) in the ≥2 500 g group. In the <1 500 g group, accuracy rates ranged from 24% to 56%, with body surface measurement showing the highest accuracy (56%); the mean difference from actual depth was－0.073 cm, with 95% limits of agreement (LOA) of－1.764 to 1.618 cm. In the 1 500-2 499 g group, accuracy rate ranged from 15% to 51%, with the modified Tambasco formula being most accurate (51%); the mean difference was 0.113 cm (95%LOA:－1.558-1.783 cm). In the ≥2 500 g group, accuracy rate ranged from 0/15 to 10/15, with Dunn's nomogram being most accurate (10/15); the mean difference was－0.120 cm (95%LOA:－1.380-1.140 cm).Conclusions:The accuracy of the nine UVC depth estimation methods varied across different BW groups and among methods within the same group. Selection of an estimation method should be tailored to the neonate's birth weight.

Objective:To analyze the clinical and genetic characteristics of children diagnosed with Noonan-syndrome associated with loose anagen hair (NS-LAH).Methods:A retrospective analysis was conducted on the clinical data of 5 children diagnosed with NS-LAH by the Endocrinology Department of the Capital Institute of Pediatrics from January 2018 to June 2024. This analysis encompassed the patients′ demographic information, clinical manifestations, distinguishing features, treatment regimens, and prognostic outcomes to elucidate their clinical characteristics. Additionally, whole-exome sequencing and Sanger sequencing were utilized to investigate the genetic etiology within the families, and the identified variations were interpreted according to the guidelines of the American College of Medical Genetics and Genomics.Results:Among the 5 NS-LAH patients, there were 3 boys and 2 girls, with ages at diagnosis ranging from 2.3 to 7.7 years old. All patients presented with short stature as a primary complaint. Birth histories were generally unremarkable, though case 2 and 5 of macrosomia were noted. In addition to the characteristic facial features of Noonan syndrome, short stature, and varying degrees of intellectual and motor developmental delay, all 5 patients exhibited sparse hair that was easily shed, as well as enlarged head circumferences. Four patients showed structural cardiac abnormalities, which included a case of hypertrophic cardiomyopathy, 2 cases of atrial septal defect, and 1 case of patent foramen ovale. Genetic analysis revealed heterozygous missense variantion in SHOC2 gene in 4 patients, comprising 3 cases with c.4A>G (p.S2G) and one case with c.519G>C (p.M173I). Additionally, one patient was found to have a heterozygous missense variantion c.146C>G (p.P49R) in PPP1CB gene. Three children were diagnosed with growth hormone deficiency and treated with growth hormone for 1.7, 2.7 and 0.5 years. This resulted in significant improvements in height, with annual increases of 11.8, 8.4 and 13.0 cm, respectively. Among the 4 patients with SHOC2 variantions, 2 developed systemic lupus erythematosus and 1 exhibited symptoms of arthritis.Conclusions:Growth failure is the primary complaint in patients with NS-LAH. Key characteristic findings include enlarged head circumference and sparse, loose hair. Growth hormone deficiency is commonly associated with NS-LAH, and growth hormone therapy is generally effective. Furthermore, patients carrying the classic variantion in SHOC2 (c.4A>G) may have an increased risk of developing autoimmune diseases.