Objective To explore the mechanism of Luzhongjiangu Decoction in treating Osteonecrosis of the femoral head(ONFH).Methods Animal experiments were conducted to validate the therapeutic effect of Luzhongjiangu Decoction on ONFH.Network pharmacology was employed to screen potential targets,and molecular docking was used to verify the affinity between ligands and receptors.Fifty rats were randomly divided into blank group,model group,high-dose Luzhongjiangu Decoction groups,medium-dose Luzhongjiangu Decoction groups and low-dose Luzhongjiangu Decoction groups.After treatment,the therapeutic effect was evaluated by bone histomorphometry,bone histopathology and the expression of osteogenic related proteins.The serum metabolic differences were detected by UHPLC-QE-MS non-targeted metabonomics technique,followed by metabolic pathway enrichment analysis.Network pharmacology and metabolomics were integrated,and molecular docking was employed to further investigate the underlying mechanisms..Results The experimental results showed that Luzhongjiangu Decoction can significantly increase the expression of OCN,OPN and other osteogenic related factors,increase bone mineral density,alleviate the destruction of bone trabeculae,compared with that in the model group(P<0.01).The metabolomics test showed that compared with model group,Luzhongjiangu Decoction could callback 34 kinds of serum metabolic differences,involving 21 metabolic pathways,the main metabolic pathways were arachidonic acid metabolism,steroid hormone biosynthesis,primary bile acid biosynthesis,lysine degradation and so on.Network pharmacological results suggested that 185 active components and 1040 targets,551 disease targets and 76 intersection targets were obtained.The key pathways of Luzhongjiangu Decoction in the treatment of ONFH,which were analyzed by KEGG,involved HIF-1 signaling pathway,thyroid hormone signaling pathway,Calcium signaling pathway and so on.Integrated analysis showed that Luzhongjiangu Decoction may treat ONFH through seven metabolic pathways including arginine and proline metabolism,arachidonic acid metabolism,and steroid hormone biosynthesis;the molecular docking results also revealed correlation between potential pharmacodynamic substances and core target genes.Conclusion Luzhongjiangu Decoction can regulate the balance between proliferation and apoptosis of bone cells in a hypoxic environment by affecting the metabolic pathways such as arachidonic acid metabolism and HIF-1 signaling pathway,thereby exerting a therapeutic effect on osteonecrosis of the femoral head.

Executive function(EF) is an advanced cognitive function of the central nervous system, and is closely related to an individual's capacity for daily living and adaptation. Patients with attention deficit hyperactivity disorder (ADHD) typically exhibit significant executive dysfunction. While most existing studies on the executive function of individuals with ADHD are cross-sectional, and little is known about the longitudinal maturation process of related brain structures and functional connectivity patterns. The findings indicate that ADHD patients exhibit differential developmental trajectories in brain structural and functional connectivity compared with typically developing group.Furthermore, there is a lifespan association between abnormal brain network development and ADHD symptoms. This article aims to elucidate the characteristics of executive function deficits in ADHD patients across different developmental stages, examining their relationship with the nervous system’s development from a development perspective.

Objective To explore the mechanism of Luzhongjiangu Decoction in treating Osteonecrosis of the femoral head(ONFH).Methods Animal experiments were conducted to validate the therapeutic effect of Luzhongjiangu Decoction on ONFH.Network pharmacology was employed to screen potential targets,and molecular docking was used to verify the affinity between ligands and receptors.Fifty rats were randomly divided into blank group,model group,high-dose Luzhongjiangu Decoction groups,medium-dose Luzhongjiangu Decoction groups and low-dose Luzhongjiangu Decoction groups.After treatment,the therapeutic effect was evaluated by bone histomorphometry,bone histopathology and the expression of osteogenic related proteins.The serum metabolic differences were detected by UHPLC-QE-MS non-targeted metabonomics technique,followed by metabolic pathway enrichment analysis.Network pharmacology and metabolomics were integrated,and molecular docking was employed to further investigate the underlying mechanisms..Results The experimental results showed that Luzhongjiangu Decoction can significantly increase the expression of OCN,OPN and other osteogenic related factors,increase bone mineral density,alleviate the destruction of bone trabeculae,compared with that in the model group(P<0.01).The metabolomics test showed that compared with model group,Luzhongjiangu Decoction could callback 34 kinds of serum metabolic differences,involving 21 metabolic pathways,the main metabolic pathways were arachidonic acid metabolism,steroid hormone biosynthesis,primary bile acid biosynthesis,lysine degradation and so on.Network pharmacological results suggested that 185 active components and 1040 targets,551 disease targets and 76 intersection targets were obtained.The key pathways of Luzhongjiangu Decoction in the treatment of ONFH,which were analyzed by KEGG,involved HIF-1 signaling pathway,thyroid hormone signaling pathway,Calcium signaling pathway and so on.Integrated analysis showed that Luzhongjiangu Decoction may treat ONFH through seven metabolic pathways including arginine and proline metabolism,arachidonic acid metabolism,and steroid hormone biosynthesis;the molecular docking results also revealed correlation between potential pharmacodynamic substances and core target genes.Conclusion Luzhongjiangu Decoction can regulate the balance between proliferation and apoptosis of bone cells in a hypoxic environment by affecting the metabolic pathways such as arachidonic acid metabolism and HIF-1 signaling pathway,thereby exerting a therapeutic effect on osteonecrosis of the femoral head.

Objective:To investigate the effects of early enteral and parenteral nutrition support on the growth, development, and metabolomics of low-birth-weight newborns.Methods:Ninety low-birth-weight newborns admitted to Hangzhou Maternity and Child Health Care Hospital from April 2022 to April 2024 were included in this retrospective study. They were randomly divided into a control group ( n = 45) and an intervention group ( n = 45) according to different intervention methods. The control group received routine traditional nutritional support, while the intervention group received early enteral and parenteral nutrition support. Data were collected on the growth and development status of the newborns, as well as their feeding conditions. Gastric fluid pH value, frequency of bowel sounds, and level of direct bilirubin were recorded. Physical condition was also assessed. The Neonatal Behavioral Neurological Assessment (NBNA) was used to evaluate the neurobehavioral status of the newborns. Additionally, the incidence of complications was recorded for both groups, and metabolomic changes were analyzed. Results:After intervention, the control group exhibited a time to regain birth weight of (20.67 ± 8.31) days, a time to reach a body weight of 2.0 kg of (53.57 ± 12.51) days, a lowest recorded body weight of (1.32 ± 0.21) kg, a body weight loss percentage of (12.31 ± 5.52)%, and a body weight gain of (15.02 ± 2.30) g/(kg/d). In contrast, the intervention group demonstrated a time to regain birth weight of (14.31 ± 5.62) days, a time to reach a body weight of 2.0 kg of (39.21 ± 9.32) days, a lowest recorded body weight of (1.01 ± 0.17) kg, a body weight loss percentage of (7.84 ± 4.92)%, and a body weight gain of (17.74 ± 3.94) g·kg?1·d?1. All differences between the two groups were statistically significant ( t = 4.28, 9.96, 7.69, 4.05, 4.11, all P < 0.001). The difference in the lowest body weight day between the two groups of children was not statistically significant ( P > 0.05). After intervention, the control group had an initial oral feeding duration of (8.30 ± 1.37) days, with a vomiting frequency of (10.25 ± 2.20) times, a daily milk intake of (35.38 ± 3.94) mL, a gastric fluid pH value of (3.85 ± 0.20), bowel sounds of (4.94 ± 0.97) times/minute, and a direct bilirubin level of (41.98 ± 25.76) mmol/L. In contrast, the intervention group showed an initial oral feeding duration of (4.01 ± 0.76) days, a vomiting frequency of (5.61 ± 1.24) times, a daily milk intake of (43.54 ± 4.07) mL, a gastric fluid pH value of (3.41 ± 0.12), bowel sounds of (5.86 ± 1.11) times/minute, and a direct bilirubin level of (28.98 ± 18.10) mmol/L. The differences between the two groups were statistically significant ( t = 18.36, 12.32, 9.66, 12.65, 4.18, 2.77, all P < 0.05). After intervention, the control group had a body length of (40.32 ± 1.84) cm, a body weight of (1.47 ± 0.55) kg, and a head circumference of (29.21 ± 1.07) cm. The intervention group had a body length of (45.00 ± 2.16) cm, a body weight of (1.83 ± 1.03) kg, and a head circumference of (30.14 ± 1.35) cm. The differences between the two groups were statistically significant ( t = 11.06, 2.06, 3.62, all P < 0.05). At 40 weeks of corrected gestational age post-intervention, the control group had a NBNA score of (30.11 ± 2.41), whereas the intervention group had an NBNA score of (34.52 ± 2.82). The difference between the two groups was statistically significant ( t = 7.97, P < 0.05). The number of patients experiencing common complications in the intervention group was lower than that in the control group [8 (17.78%) vs. 28 (62.22%), χ2 = 18.51, P < 0.05]. The control group had glycine levels of (94.07 ± 19.78) μmol/L, valine levels of (99.53 ± 13.42) μmol/L, homocysteine levels of (10.87 ± 4.43) μmol/L, cystatin levels of (233.71 ± 35.02) μmol/L, and methionine levels of (20.54 ± 4.67) μmol/L. The intervention group had glycine levels of (79.21 ± 17.54) μmol/L,valine levels of (88.70 ± 12.96) μmol/L, homocysteine levels of (13.68 ± 7.66) μmol/L, cystatin levels of (256.54 ± 35.49) μmol/L, and methionine levels of (22.97 ± 5.49) μmol/L. The differences between the two groups were statistically significant ( t = 3.77, 3.89, 2.13, 3.07, 2.26, all P < 0.05). Conclusions:Early enteral and parenteral nutritional support for low-birth-weight infants can restore their growth and development status, improve feeding conditions, enhance gastrointestinal function, and improve levels of metabolomic-related indicators.

Executive function(EF) is an advanced cognitive function of the central nervous system, and is closely related to an individual's capacity for daily living and adaptation. Patients with attention deficit hyperactivity disorder (ADHD) typically exhibit significant executive dysfunction. While most existing studies on the executive function of individuals with ADHD are cross-sectional, and little is known about the longitudinal maturation process of related brain structures and functional connectivity patterns. The findings indicate that ADHD patients exhibit differential developmental trajectories in brain structural and functional connectivity compared with typically developing group.Furthermore, there is a lifespan association between abnormal brain network development and ADHD symptoms. This article aims to elucidate the characteristics of executive function deficits in ADHD patients across different developmental stages, examining their relationship with the nervous system’s development from a development perspective.

Objective:To develop a rapid assessment scale for healthy aging suitable for the Chinese population.Methods:Based on existing healthy aging assessment scales, national standards, and expert consensus, an initial Healthy Aging Rapid Assessment Scale was drafted through two rounds of expert consultation. A pre-survey was conducted with 3 220 subjects recruited from Guangzhou between July 2023 and July 2024. Items were screened through item analysis and exploratory factor analysis to form the final scale. Reliability and validity of the final scale were validated across five cities: Guangzhou, Dongguan, Shenzhen, Baoding, and Chuxiong.Results:The initial version comprised 36 items, while the finalized scale contained 18 items across three dimensions: metabolic health, mental health, and cognitive health. Test-retest reliability ranged from 0.71 to 0.81 across all study sites. The Spearman-Brown coefficient varied between 0.91-0.96, Cronbach′s α between 0.77-0.83, comparative fit index (CFI) between 0.90-0.98, goodness-of-fit index (GFI) between 0.90-0.99, and root-mean-square error of approximation (RMSEA) between 0.03-0.09. For the three dimensions, reliability and validity metrics demonstrated consistency: Spearman-Brown coefficients 0.87-0.99, Cronbach′s α 0.77-0.83, CFI 0.90-0.98, GFI 0.90-0.99, and RMSEA 0.03-0.09 across four regions.Conclusion:The developed Healthy Aging Rapid Assessment Scale for the Chinese population exhibits robust reliability and validity.

Objective:To explore the value of ultrasound imaging characteristics combined with clinical indicators in assessing the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC).Methods:A retrospective analysis was conducted for patients who underwent pancreatic contrast-enhanced ultrasound (CEUS) from September 2017 to October 2023 at Peking Union Medical College Hospital and were diagnosed with PDAC based on pathological findings. Various parameters were recorded, including CA19-9 levels, tumor size, location, morphologic features, echogenicity, presence of internal cystic components, dilatation of the main pancreatic duct, peripheral vascular invasion, CEUS characteristics, presence or absence of liver metastasis, and treatment methods. In April 2024, patient survival information was obtained through telephone follow-up or review of medical records. Based on the results of the cox regression model analysis, a nomogram model of the risk of death was developed. The receiver operating characteristic (ROC) curves were applied to evaluate the predictive efficacy of the model. The calibration curves were plotted to evaluate the accuracy of the model, and clinical decision curves were used to evaluate the clinical benefit of the model.Results:This study included a total of 207 patients with PDAC. As of April 2024, 71 patients were alive and 136 died, with a median survival time of 14 months (95% CI: 12 -17). Multivariate analysis confirmed that the elevated CA19-9 ( HR=1.689, 95% CI: 1.102-2.588), tumor size >4 cm ( HR=1.641, 95% CI: 1.159-2.322), taller-than-wide shapes ( HR=1.450, 95% CI: 1.019-2.065), incomplete hypo-enhancement ( HR=1.618, 95% CI: 1.100-2.380), and liver metastasis ( HR=1.687, 95% CI: 1.175-2.423) were independent risk factors for survival in patients with PDAC. A nomogram model was further constructed for 6-month, 12-month and 3-year survival of patients with PDAC. The areas under the ROC curve were 0.679, 0.705 and 0.815, respectively. The calibration curves suggested that the model was more accurate, and the clinical decision curves showed that the model had a better clinical benefit. Conclusion:The combined use of ultrasound imaging characteristics and clinical indicators could effectively predict the prognosis of PDAC patients. Specifically, tumor size >4 cm, taller-than-wide shapes, incomplete hypo-enhancement, elevated CA19-9, and the presence of liver metastasis are correlated with poorer survival outcomes. The nomogram model constructed on the basis of these factors can be used to assess the survival of patients with PDAC.

Objective To analyze the acupoint selection law of acupuncture and moxibustion for postherpetic neuralgia(PHN)with R language data mining technology.Methods The clinical research literature on acupuncture and moxibustion treatment of PHN included in CNKI,Wanfang Data,VIP and CBM from January 1,2010 to July 1,2023 was retrieved,and the database was established by Excel 2016.R language was used to statistically analyze the frequency of acupoint usage,meridians,locations,specific acupoints,etc.Through association rule analysis and clustering analysis,the characteristics and law of acupoint selection for acupuncture and moxibustion treatment of PHN were obtained.Results A total of 198 articles were included,including 83 acupoints,with a total frequency of 714 times.The high-frequency acupoints include Ashi acupoint,Jiaji acupoint and Yanglingquan.The commonly used meridians were gallbladder meridian,spleen meridian and large intestine meridiam.The acupoints were mostly in the upper and lower limbs,with the Wushu acupoints,Yuan acupoints and Xiahe acupoints being the most common.The core acupoint was Ashi acupoint,Jiaji acupoint,Hegu,Quchi,and 9 sets of association rules and 5 effective clusters were obtained.Conclusion The most commonly used acupoints for acupuncture and moxibustion treatment of PHN are Ashi acupoint,Jiaji acupoint,Hegu and Quchi,which mainly follow the principle of combining local acupoint selection with distal acupoint selection.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

Objective To investigate the predictive value of combined radiomic features derived from chest CT scans with clinical characteristics for epidermal growth factor receptor(EGFR)gene mutations in non-small cell lung cancer(NSCLC).Methods A multi-center case-control study was conducted on the clinical data and CT images of 1 070 NSCLC patients from the radiology departments of the 3 medical institutions between January 2013 and October 2023.The 719 NSCLC patients from the First Affiliated Hospital of Army Medical University were randomly divided into a training set and an internal validation set in a ratio of 7∶3;The 173 patients in the Eastern Theatre General Hospital and the 178 patients in Army Medical Centre of PLA were assigned into the external validation set 1 and 2,respectively.Least absolute shrinkage and selection operator(LASSO)regression was employed to identify the optimal radiomic features,which were subsequently used to construct a radiomics model.Univariate and multivariate logistic regression analyses were applied to identify clinical features associated with EGFR mutation,thereby developing a clinical model.The radiomic and clinical features were subsequently combined to develop a comprehensive model.All the 3 classification models were built using random forest(RF)machine learning.The area under curve(AUC),accuracy,sensitivity and specificity were utilized to evaluate the predictive performance of the models.Calibration curve was plotted to assess the goodness of fit of the comprehensive model,while decision curve analysis was performed to assess the clinical utility of the model.Results The AUC value of the radiomics model was 0.762 4(95%CI:0.692 4～0.825 1),0.745 4(95%CI:0.671 1～0.814 3),and 0.724 7(95%CI:0.639 7～0.801 6),respectively,in the internal validation set,external validation set 1,and external validation set 2;The AUC value of the clinical prediction model was 0.691 7(95%CI:0.627 9～0.757 6),0.652 5(95%CI:0.576 7～0.729 1),and 0.779 2(95%CI:0.712 5～0.847 3),respectively in the above sets in turn;The comprehensive model constructed based on clinical features and radiomic features showed the best predictive efficacy,with an AUC value of 0.818 0(95%CI:0.757 7～0.874 3),0.782 4(95%CI:0.703 1～0.848 2),and 0.796 6(95%CI:0.718 1～0.868 6),respectively in the above sets.Calibration curve analysis indicated that the comprehensive model had a good fit,while decision curve analysis revealed that the model provided a favorable net benefit.Conclusion Our comprehensive model constructed based on chest CT radiomic features and clinical characteristics shows superior predictive performance for EGFR gene mutations in NSCLC across multiple center datasets,which may be helpful for clinical decision-making for treatment strategies.