Eignt compounds were isolated from the roots of Alinarubella Hance. They were identified as quinovic acid(Ⅰ), 3-oxo-urs-12-ene-27, 28-dioic acid (Ⅱ). quinovic acid-3? -O-?-D-glucopyranoside(Ⅲ ), quinovie acid-3?-O-?-L-rhamnopyranoside(Ⅳ). noreugenin (Ⅴ ), 7 -O-?-D-glucosyl- noreugenin(Ⅵ), scopo letin(Ⅶ), daucosterol(Ⅷ), by means of spectral analysis and reactions, Ⅱ, Ⅲ snd Ⅳ are isolated from the genus adina for the first time.

Objective To investigate the application of MRI targeting contrast agent ( P-Gd-Probe) for P selectin in evaluating the severity grades of acute pancreatitis (AP).Methods L-arginine solution (100mg/100kg) were intraperitoneally injected for 3 times once an hour to establish AP model in SD rats. Control group was injected with normal saline in a equal volume .All rats were divided into acute edematous pancreatitis (AEP) group (6 h and 12 h after model establishment)and acute necrotizing pancreatitis (ANP) group (24 h and 48 h after model establishment ) based on the pathology .The rats were examined by T 1 WI plain and enhanced scanning at 6 h, 12 h, 24 h and 48 h after injection , and P-Gd-probe was as the enhanced contrast agent.The signal noise ratio ( SNR) of the pancreas were measured before and after enhancement .Then the pancreas tissues were harvested for pathological examination and P selectin expression in pancreatic tissue was detected using immunohistochemical analysis .Results Inflammation was observed in pancreatic tissue at 6h after establishment , and became more serious as the modeling time extended .P selectin expression was increased as pancreatitis inflammation became more serious .The SNR of control group was stable before and after enhancement.The SNR before and after enhancement was 17.22 ±1.35 and 37.38 ±1.66 in AEP group, and 16.29 ±1.39 and 58.18 ±1.03 in ANP group.The SNR after enhancement was higher than that before enhancement, and the differences were significantly different ( t=-49.59 and -86.09, P<0.001 ). Conclusions Monoclonal antibody MRI contrast agent targeting P selectin is helpful in evaluating the severity of AP.

Objective To investigate the influencing factor of the morphology of unruptured intracranial aneurysms for aneurysm wall enhancement under the high-resolution magnetic resonance imaging. Methods From January 2015 to December 2016,the clinical and imaging data of 68 consecutive patients with unruptured intracranial aneurysm (86 aneurysms) in Changhai Hospital,the Second Military Medical University were enrolled retrospectively. Vascular wall imaging technology was used to conduct aneurysm scan,and the aneurysm wall enhancement was identified by the imaging features before and after contrast enhancement. They were divided into either an enhancement group ( n=32,34 aneurysms) or a non-enhancement group (n=45,52 aneurysms) according to whether having the abnormal enhancement of aneurysm wall or not ( because some patients also have enhanced aneurysms and non-enhanced aneurysms, the number of cases of the enhanced or not was calculated seperately in both groups ) . Morphological parameters were calculated by 3D image data,including aneurysm size,ratio of height to width,volume ratio, dome-to-neck ratio, transverse length ratio, bottleneck factor, and inflow angle. Univariate and multivariate logistic analyses were used to determine the morphological influence factors of aneurysm wall enhancement. Results (1) A total of 34 (39. 5%) aneurysms had aneurysm wall enhancement and 52 (60. 5％) aneurysms did not have aneurysm wall enhancement. There were no significant differences in sex, age, hypertension,diabetes, smoking, family history of subarachnoid hemorrhage, and aneurysm site in both groups (all P>0. 05). (2) The aneurysm size,ratio of height to width,volume ratio,dome-to-neck ratio, and bottleneck factor in the enhancement group were larger than those of the non-enhancement group. There were significant differences between the 2 groups (9. 19 [6. 54,11. 04] mm vs. 5. 31 [4. 17,7. 37] mm, (1. 18 [1. 01,1. 69] vs. 0. 91 [0. 72,1. 25],(3. 62 [2. 30,4. 63] vs. 2. 18 [1. 37,2. 76],1. 52 [1. 25, 1. 99] vs. 1. 19 [1. 03,1. 51],and 1. 21 [1. 11,1. 69] vs. 1. 05 [0. 94,1. 31],all P<0. 01). The proportion of irregular morphologic aneurysms in the enhancement group was higher than that in the non-enhancement group. There was significant difference between the 2 groups (55. 9％ [19/34] vs. 17. 3％ [9/52],P<0. 01 ) . There were no significant differences in transverse length ratio and inflow angle between the 2 groups (all P>0. 05). (3) Because the ratio of height to width,volume ratio,dome-to-neck ratio,and bottleneck factor were related to the aneurysm size,the aneurysm size,inflow angle,and irregular shape were included in the multivariate logistic regression analysis. The results showed that aneurysm size ( OR,3. 727,95％CI 1. 933-6. 971,P<0. 01) and irregular shape (OR,3. 990,95％CI 1. 219-13. 065,P=0. 022) were the independent risk factors for aneurysm wall enhancement. Conclusions The size and irregular shape of unruptured intracranial aneurysms are the independent risk factors for aneurysm wall enhancement. High-resolution magnetic resonance wall imaging may become an effective and noninvasive imaging method for evaluating the ruptured risk of intracranial aneurysms.

Objective:To analyze the clinical characteristics of children aged two years old and above with respiratory syncytial virus (RSV) infection in pediatric intensive care unit (PICU).Methods:Children who had RSV infection admitted to PICU at Children′s Hospital of Zhengzhou University from March 2019 to December 2021 were divided into older age group(≥two years old) and younger age group(0.05); In younger age group, there were 132(64.8%) cases of fever and 125(64.8%) cases of wheezing; In older age group, there were 31(93.9%) cases of fever and 13(39.4%) cases of wheezing; the incidence of fever was higher in older age group than that in younger age group( χ2=9.147, P<0.05), and the incidence of wheezing was lower than that in younger age group( χ2=7.631, P<0.05), and the differences were statistically significant.(2) There were 15 (45.5%) cases of simple infection and 18 (54.5%) cases of mixed infection in older age group, and the P/F was significantly different between children with simple infection and those with mixed infection ( P<0.05); there were 14 (42.4%) cases of combined underlying diseases and 19 (57.6%) cases without underlying diseases, and the length of stay in PICU was different between children with combined underlying diseases and those without underlying diseases ( P<0.05), and there was no significant difference in mechanical ventilation or total length of stay ( P>0.05). Conclusion:RSV infection in children aged two years old and above in PICU occurres mostly between two and six years of age, with a relatively low incidence of wheezing and common fever; RSV infection alone may have a greater impact on oxygenation, and combined underlying diseases can affect the length of stay in PICU.

Objective:To understand the early clinical characteristics and drug sensitivity results of children died of invasive pneumococcal disease (IPD) in Pediatric Intensive Care Unit (PICU) so as to guide the early clinical identification and treatment.Methods:The early clinical data and drug sensitivity result of children died of IPD in PICU of the Children′s Hospital, Zhengzhou University and Beijing Children′s Hospital, Capital Medical University from May 2015 to May 2019 were retrospectively analyzed.Results:A total of 18 children meeting the criteria were enrolled, including 6 males and 12 females.The median age was 1 year and 9 months (ranged from 2 months and 20 days to 6 years and 7 months), there were 2 cases(11.1%) > 5 years old, and 16 cases(88.9%)≤ 5 years old.There were 17(94.4%) children related to community acquired infection.Among 18 cases, the first symptom was intracranial infection in 10 cases (55.6%), bloodstream infection in 4 cases (22.2%), and pulmonary infection in 3 cases (16.7%). There were 5 cases complicated with virus infection at the same time.Auxiliary examination: all of the 18 cases had anemia and hypoalbuminemia, and 15 cases(93.8%) had HCO 3- reduction.White blood cells(WBC), platelets(PLT) and natural killer (NK) cell decreased in 7 cases (7/18 cases), 12 cases (12/18 cases) and 6 cases (5/16 cases), respectively, but C-reactive protein(CRP), procalcitonin (PCT), lactic acid concentration(LAC), D-dimer (D-Di), international normalized ratio (INR) and B-type natriuretic peptide (BNP) were increased in 12 cases (12/18 cases), 14 cases (14/18 cases), 7 cases (7/17 cases), 14 cases (14/17 cases) and 9 cases (9/9 cases), respectively.Six children(33.3%) did not receive the treatment of sensitive antibiotics before admission.According to the drug sensitivity results: all the 18 strains had multiple-drug resistance(MDR), and the resistance rates of Penicillin, Erythromycin, Tetracycline, Clindamycin and Sulfamethoxazole were 22.2%, 100.0%, 100.0%, 100.0% and 94.4%, respectively, all the strains were sensitive to Vancomycin, Linezolid and Levofloxacin. Conclusions:Most of the children died of IPD in PICU are of community-acquired infection and less than 5 years old.Anemia and hypoalbuminemia are common in the dead children.The decreased in HCO 3- and increased PCT, LAC and D-Di in the early stage might be related to poor prognosis of patients.Most of the children died of IPD are infected with MDR strains.

Objective:To develop and validate the models based on mixed enhanced computed tomography (CT) radiomics and deep learning features, and evaluate the efficacy for differentiating pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC) before surgery.Methods:The clinical data of 201 patients with surgically resected and histopathologically confirmed PASC (PASC group) and 332 patients with surgically resected histopathologically confirmed PDAC (PDAC group) who underwent enhanced CT within 1 month before surgery in the First Affiliated Hospital of Naval Medical University from January 2011 to December 2020 were retrospectively collected. The patients were chronologically divided into a training set (treated between January 2011 and January 2018, 156 patients with PASC and 241 patients with PDAC) and a validation set (treated between February 2018 and December 2020, 45 patients with PASC and 91 patients with PDAC) according to the international consensus on the predictive model. The nnU-Net model was used for pancreatic tumor automatic segmentation, the clinical and CT images were evaluated, and radiomics features and deep learning features during portal vein phase were extracted; then the features were dimensionally reduced and screened. Binary logistic analysis was performed to develop the clinical, radiomics and deep learning models in the training set. The models' performances were determined by area under the ROC curve (AUC), sensitivity, specificity, accuracy, and decision curve analysis (DCA).Results:Significant differences were observed in tumor size, ring-enhancement, upstream pancreatic parenchymal atrophy and cystic degeneration of tumor both in PASC and PDAC group in the training and validation set (all P value <0.05). The multivariable logistic regression analysis showed the tumor size, ring-enhancement, dilation of the common bile duct and upstream pancreatic parenchymal atrophy were associated with PASC significantly in the clinical model. The ring-enhancement, dilation of the common bile duct, upstream pancreatic parenchymal atrophy and radiomics score were associated with PASC significantly in the radiomics model. The ring-enhancement, upstream pancreatic parenchymal atrophy and deep learning score were associated with PASC significantly in the deep learning model. The diagnostic efficacy of the deep learning model was highest, and the AUC, sensitivity, specificity, and accuracy of the deep learning model was 0.86 (95% CI 0.82-0.90), 75.00%, 84.23%, and 80.60% and those of clinical and radiomics models were 0.81 (95% CI 0.76-0.85), 62.18%, 85.89%, 76.57% and 0.84 (95% CI 0.80-0.88), 73.08%, 82.16%, 78.59% in the training set. In the validation set, the area AUC, sensitivity, specificity, and accuracy of deep learning model were 0.78 (95% CI 0.67-0.84), 68.89%, 78.02% and 75.00%, those of clinical and radiomics were 0.72 (95% CI 0.63-0.81), 77.78%, 59.34%, 65.44% and 0.75 (95% CI 0.66-0.84), 86.67%, 56.04%, 66.18%. The DCA in the training and validation sets showed that if the threshold probabilities were >0.05 and >0.1, respectively, using the deep learning model to distinguish PASC from PDAC was more beneficial for the patients than the treat-all-patients as having PDAC scheme or the treat-all-patients as having PASC scheme. Conclusions:The deep learning model based on CT automatic image segmentation of pancreatic neoplasm could effectively differentiate PASC from PDAC, and provide a new non-invasive method for confirming PASC before surgery.

The pollution caused by improper handling of plastics has become a global challenge. In addition to recycling plastics and using biodegradable plastics, an alternative solution is to seek efficient methods for degrading plastics. Among them, the methods of using biodegradable enzymes or microorganisms to treat plastics have attracted increasing attention because of its advantages of mild conditions and no secondary environmental pollution. Developing highly efficient depolymerizing microorganisms/enzymes is the core for plastics biodegradation. However, the current analysis and detection methods cannot meet the requirements for screening efficient plastics biodegraders. It is thus of great significance to develop rapid and accurate analysis methods for screening biodegraders and evaluating biodegradation efficiency. This review summarizes the recent application of various commonly used analytical techniques in plastics biodegradation, including high performance liquid chromatography, infrared spectroscopy, gel permeation chromatography, and determination of zone of clearance, with fluorescence analysis techniques highlighted. This review may facilitate standardizing the characterization and analysis of plastics biodegradation process and developing more efficient methods for screening plastics biodegraders.
Biodegradable Plastics/chemistry* ; Biodegradation, Environmental

Objective: To retrospectively analyse the genetic characteristics, diagnosis, treatment and prognosis of special AT-rich binding protein 2 (SATB2)-associated syndrome. Methods: Clinical data of one case of SATB2-associated syndrome diagnosed in Children′s Hospital Affiliated to Zhengzhou University in January 2018, were collected including clinical test, treatment plan, follow-up outcomes. The clinical characteristics of SATB2-associated syndrome were analyzed, and literature review was conducted. Results: The female proband, eight-year-old, were admitted with the clinical manifestations including epilepsy seizures, delayed language development, sparse hair, long face, prominent forehead, long nose, lower eyelid cleft oblique, low ear, smooth philtrum, small mandible, sparse teeth arrangement, and lack of some teeth. The intelligence quotient score was 49. The brain magnetic resonance imaging showed myelinated dysplasia. Long-range video-electroencephalography showed spike-wave activity, slow spike-wave discharges in the bilateral middle and posterior temporal regions. The trio whole exome sequencing (trio WES) test showed that the proband carried a heterozygous nonsense mutation c.1300 C>T (p.Gln434Ter) in the SATB2 gene, and the muation was de novo comfirmed by pedigree analysis. Thirty-seven literatures relevant to SATB2-associated syndrome, from January 1989 to June 2019, were retrieved. Threre were 23 overseas literatures and one domestic report, including a total number of 158 cases. There were 49 missense mutations, 38 nonsense mutations, 32 frameshift mutations, seven splicing-site mutations, six translocation mutations, one insertion mutation, 22 gene-deletions and three gene-duplications. Among the 158 reported cases, 90 were male and 62 female, sex was not described in six cases. One hundred and fifty-eight (100.0%) patients had mental retardation, 44 (30.6%) with growth retardation, 107 (84.3%) with facial deformities, 70 (45.5%) with cleft palate, 135 (98.5%) with dental abnormalities, 66 (43.4%) with language retardation, 29 (20.0%) with epileptic seizures, and 50 (46.3%) with neuroimaging abnormalities. Conclusions The main clinical manifestations of SATB2-related syndromes are severe developmental retardation, low intelligence, delayed language development, language deficiency, high palatal arch and cleft palate, rare epilepsy seizures, dental anomalies and scant hair. The study identified a novel nonsense mutation c. 1300 C>T (p. Gln434Ter) in the SATB2 gene, which is responsible for the development of SATB2-associated syndrome.