Objective To analyse the effect of specimen storage time on platelet count in apheresis Donors,in order to choose the appropriate testing time.Methods We choose fifty healthy Unpaid Blood Donors of Platelets to test platelet count in 0,0.5,1,3,6h respectively by the blood counting instrument.Results At room temperature,the count of platelets from blood samples is relatively lower at 0 hour and the difference is significant (P ＜ 0.05).After 0.5-6 hours,the count of platelets become stabilized and not has significantly different(P＞0.05).Conclusion The count of platelets of blood samples is lower at 0 hour than 0.5-6 hours,this work suggest that the count of platelets of blood samples should be done at 0.5-6 h in order to protect platelets quality.

Objective To investigate the methods of isolation,culture,identification and labeling of mesenchymal stem cells(MSCs) in vitro and lay a foundation for further study on intervention of MSCs on immunologic rejection of organ transplantation. Methods MSCs were isolated and cultivated by adherent methods . The expressions of CD90 and CD45 of cells were analyzed by using flow cytometry in order to identify MSCs.The third generation of MSCs were labeled by DAPI,the labeling efficiency was detected.Results Primary cultured MSCs adhered to plastic surface within 48 h and reached 90% confluence within 7-10 d .Flow cytometry showed that the positive rates of CD90 and CD45 of MSCs at third generation were 99.8% and 6.8%. MSCs expressed CD90 but no CD45.All of the MSCs after labeling by DAPI showed blue fluorescence by immunofluoroscope. DAPI labeling was sensitive and highly efficient to MSCs.Conclusion Adherent method is simple and easy to isolate and cultivate MSCs and it can serve as a routine method.DAPI labeling can be used as a efficient method to label MSCs.

Objective:To explore and compare the clinical efficacy of lyophilized recombinant human brain natriuretic peptide (Lrh-BNP) and dobutamine (Dob) in the treatment of patients with acute heart failure (AHF) and impacts on the plasma galectin (Gal)-3,Cystatin C (CysC) and endothelin (ET-)-1 levels.Methods:114 cases of patients with AHF in our hospital from February 2015 to February 2017 were selected as the research objectives and randomly divided into two groups.Dob group was treated by Dob,while Lrh-BNP group was treated by Lrh-BNP.The cardiac function parameters,plasma Gal-3,CysC,ET-1 levels before and after treatment,clinical comprehensive efficacy and incidence of adverse reactions were compared between two groups.Results:The FS,LVEF levels of both groups at 72 hours after treatment were significantly higher than those before treatment (P＜0.01),but the LVEDD,plasma Gal-3,CysC,ET-1 levels were obviously decreased (P＜0.01),the index mentioned above of Lrh-BNP group improved more significantly than those of the Dob group(P＜0.01).The overall effective rate of Lrh-BNP group was 89.5 ％,which was significantly higher than that of the Dob group (73.7％,P＜0.05).No significant difference was found in the incidence of adverse reaction between two groups(P＞0.05).Conclusion:Lyophilized recombinant human brain natriuretic peptide was more effective in the treatment of AHF than Dobutamine with equal safety,which might be related to the decrease of plasma Gal-3,CysC,ET-1 levels.

Objective To compare artificial intelligence-assisted diagnostic system and conventional manual CT image interpretation for detection of positive pulmonary nodules and differential diagnosis of benign and malignant pulmonary nodules, and to provide a reference for the application of artificial intelligence in clinical screening for lung cancer. Methods Patients who underwent chest CT scans for pulmonary nodules from March 2019 to December 2023 were enrolled. The CT images were subjected to artificial intelligence-based and conventional manual CT image interpretation. The pathological examination results of pulmonary lesions served as a gold standard for comparison of artificial intelligence-based and conventional manual CT image interpretation in detection rate of positive pulmonary nodules and differential diagnosis of benign and malignant pulmonary nodules. Results A total of 327 positive pulmonary nodules were identified in 207 patients. The detection rate of positive pulmonary nodules was significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation (95.72% vs. 86.85%; χ²=16.16, P < 0.01). Moreover, artificial intelligence-based CT image interpretation showed significantly higher detection rates for solid (χ²=7.71, P < 0.01) and ground-glass pulmonary nodules (χ²=5.80, P < 0.05) than conventional manual CT image interpretation. The detection rates for pulmonary nodules with < 1 cm (χ²=4.97, P < 0.05), 1 to < 2 cm (χ²=7.04, P < 0.01), and 2 to < 3 cm (χ²=4.91, P < 0.05) diameters were significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for differential diagnosis of benign and malignant pulmonary nodules were 98.08%, 91.53%, 95.33%, 96.43%, and 95.71% with artificial intelligence-based CT image interpretation and 91.34%, 77.97%, 87.96%, 32.62%, and 86.50% with conventional CT image interpretation. The sensitivity (χ²=4.70, P < 0.05), specificity (χ²=4.20, P < 0.05), negative predictive value (χ²=65.28, P < 0.01), and accuracy (χ²=8.52, P < 0.01) were significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation. However, there was no significant difference in the positive predictive value (χ²=3.80, P > 0.05). Conclusion Compared with conventional manual CT image interpretation, artificial intelligence-assisted diagnostic system for CT image interpretation can significantly increase the detection rate of positive pulmonary nodules and improve the efficiency of differential diagnosis of benign and malignant pulmonary nodules, so it deserves widespread applications in physical examination and early screening for lung cancer.

Objective To compare artificial intelligence-assisted diagnostic system and conventional manual CT image interpretation for detection of positive pulmonary nodules and differential diagnosis of benign and malignant pulmonary nodules, and to provide a reference for the application of artificial intelligence in clinical screening for lung cancer. Methods Patients who underwent chest CT scans for pulmonary nodules from March 2019 to December 2023 were enrolled. The CT images were subjected to artificial intelligence-based and conventional manual CT image interpretation. The pathological examination results of pulmonary lesions served as a gold standard for comparison of artificial intelligence-based and conventional manual CT image interpretation in detection rate of positive pulmonary nodules and differential diagnosis of benign and malignant pulmonary nodules. Results A total of 327 positive pulmonary nodules were identified in 207 patients. The detection rate of positive pulmonary nodules was significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation (95.72% vs. 86.85%; χ²=16.16, P < 0.01). Moreover, artificial intelligence-based CT image interpretation showed significantly higher detection rates for solid (χ²=7.71, P < 0.01) and ground-glass pulmonary nodules (χ²=5.80, P < 0.05) than conventional manual CT image interpretation. The detection rates for pulmonary nodules with < 1 cm (χ²=4.97, P < 0.05), 1 to < 2 cm (χ²=7.04, P < 0.01), and 2 to < 3 cm (χ²=4.91, P < 0.05) diameters were significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for differential diagnosis of benign and malignant pulmonary nodules were 98.08%, 91.53%, 95.33%, 96.43%, and 95.71% with artificial intelligence-based CT image interpretation and 91.34%, 77.97%, 87.96%, 32.62%, and 86.50% with conventional CT image interpretation. The sensitivity (χ²=4.70, P < 0.05), specificity (χ²=4.20, P < 0.05), negative predictive value (χ²=65.28, P < 0.01), and accuracy (χ²=8.52, P < 0.01) were significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation. However, there was no significant difference in the positive predictive value (χ²=3.80, P > 0.05). Conclusion Compared with conventional manual CT image interpretation, artificial intelligence-assisted diagnostic system for CT image interpretation can significantly increase the detection rate of positive pulmonary nodules and improve the efficiency of differential diagnosis of benign and malignant pulmonary nodules, so it deserves widespread applications in physical examination and early screening for lung cancer.

OBJECTIVETo study the expressions of Notch1-4 gene in human keloid-derived mesenchymal-like stem cells, and to explore the Notch signaling pathway's role in the formation of keloid.

METHODSKeloid samples were collected to harvest human keloid-derived mesenchymal-like stem cells through two-step enzymatic dissociation method. By flow cytometry, cell phenotype of primary and P3 generation were analyzed. By immunocytochemistry, the expressions of Oct4, vimentin and CK19 were examined. Keloid-derived mesenchymal-like stem cells were induced into osteoblasts in vitro and calcium deposition was detected by Alizarin red S stain. Realtime polymerase chain reaction (RT-PCR) was used to detect the expressions of Notch1-4 mRNA in keloid-derived mesenchymal-like stem cells.

RESULTSFlow cytometry showed that keloid-derived mesenchymal-like stem cells of primary and P3 generation highly expressed CD29, CD44, CD90 from the typical MSC phenotype marker, but they failed to express HSC phenotype markers, such as CD34 and CD45. The results of immunocytochemistry showed that Oct4 from pluripotent stem cell markers and vimentin from mesenchymal cell markers was positive and CK19 from epithelial cell markers was negative. After induced differentiation into osteoblasts in vitro after 21 day, calcium nodules could be seen clearly; Notch1-4 gene were expressed in keloid-derived mesenchymal-like stem cells through RT-PCR. The relative quantitative of Notch2, Notch3 gene were higher than Notch1, Notch4 gene (P < 0.05).

CONCLUSIONSThe expression difference of different subtypes from Notch gene in human keloid-derived mesenchymal-like stem ceils may be related to self-renewal, proliferation, differentiation, and participate in the formation of keloid.

Adolescent ; Cells, Cultured ; Child ; Female ; Humans ; Keloid ; metabolism ; pathology ; Male ; Mesenchymal Stromal Cells ; metabolism ; Receptors, Notch ; metabolism

A global quality control method based on high performance liquid chromatography (HPLC) coupled with diode array detection (DAD), single quadrupole mass spectrometry (MS) and time-of-flight mass spectrometry (TOFMS) was developed for simultaneous determination of seven major components (mangiferin, neomangiferin, timosaponin E1, timosaponin E, timosaponin BⅡ, timosaponin BⅢ, and timosaponin AⅢ) and identification of most components in extracts of Rhizoma Anemarrhenae (RA). HPLC analysis was performed on an Agilent SB-C18 column (4.6 mm×150 mm, 5 μm) by gradient elution using acetonitrile and water-acetic acid(100∶0.05, v/v) as the mobile phase. Seven major components in RA were successfully separated. This quantitative method was fully validated in respect of the following performance criteria: linearity, precision, repeatability, stability, accuracy, limits of detection (LOD) and quantification (LOQ). A formula database of known compounds in RA was established, against which, most of the reported components in this herbal extract were identified effectively based on the extract masses acquired by TOFMS. This qualitative and quantitative method was successfully used to analyze the components in 10 batches of RA samples collected from different regions in China. This global quality control method, which consisted of HPLC-DAD-MS assay of seven major components and unambiguous identification of nineteen components, is suitable for routine quantification and comprehensive quality control of RA.

A comparison of the volatile compounds in Rhizomes Curcumae （Ezhu） and Radix Curcumae （Yujin） was undertaken using gas chromatography mass spectrometi-y （GC-MS）. Ultrasonic extraction and GC-MS methods were developed for the simultaneous determination of five sesquiterpenes, namely, α-pinene, β-elemene, curcumol, germacrone and curdione, in Ezhu and Yunjin. Good linearity （r〉0.999） and high inter-day precision were observed over the investigated concentration ranges. The validated method was successfully used for the simultaneous determination of five sesquiterpenes in Ezhu and Yujin. The quantitative method can be effectively used to evaluate and monitor the quality of Chinese curcuma in clinical use.

ObjectiveThe aim of this study is to analyze the etiology and status of bone age of children with short stat-ure.MethodsAnthropological and physical examination data were retrospectively collected and studied in 2132 children with short stature in the department of endocrinology between 2009 and 2014. Growth hormone (GH) levels were determined by ar-ginine-clonidine test. Bone age was determined by CHN scoring.ResultsAmong the 2132 patients, 1333 were males and 799 were females. Mean age is 9.03 ± 3.04 years old, mean bone age is 6.81 ± 3.05 years. Of them, 324 cases (15.2%) were diagnosed complete GH deifciency, 780 cases (36.59%) were partial GH deifciency, 27cases (1.27%) were multiple pituitary hormone de-ifciency, 13 cases (1.64%) were hypothyroidism, 893 cases (41.89%) were idiopathic short stature, 19 cases (0.89%) were small for gestational age (SGA), 40 cases (1.88%) were chromosomal disorders, etc. Signiifcant difference in age and bone age was found using t test (P<0.05). Signiifcant differences in Δage were found between etiological categories using ANOVA (P=0.000). Δage was signiifcantly and negatively associated with peak GH using Pearson's correlation.ConclusionsGH deifciency is the most common cause of short stature. Bone age of children with short stature is commonly delayed. Δage was signiifcantly and negatively associated with peak GH. Multiple pituitary hormone deifciency has a signiifcant effect on bone age. The etiology of patients with short stature cannot be determined just by bone age.

A comparison of the volatile compounds in Rhizomes Curcumae (Ezhu) and Radix Curcumae (Yujin) was undertaken using gas chromatography-mass spectrometry (GC-MS).Ultrasonic extraction and GC-MS methods were developed for the simultaneous determination of five sesquiterpenes,namely,α-pinene,β-elemene,curcumol,germacrone and curdione,in Ezhu and Yunjin.Good linearity (r＞0.999) and high inter-day precision were observed over the investigated concentration ranges.The validated method was successfully used for the simultaneous determination of five sesquiterpenes in Ezhu and Yujin.The quantitative method can be effectively used to evaluate and monitor the quality of Chinese curcuma in clinical use.