Objective To investigate the influence of ocular residual astigmatism (ORA) on the correction of astigmatism by FS-LASIK with vector analysis.Methods The records of 182 patients who had accept FS-LASIK between January,2016 and April,2016 were retrosepectively reviewed.The patients whose ORA ≥ refractive cylinder were assigned to high ocular residual astigmatism group (HORA group),ORA ＜ refractive cylinder were assigned to low ocular residual astigmatism group (LORA group).All of the patients were followed 6 months or more.The visual acuity,error ratio and correction ratio were compared between HORA group and LORA group.Results The preoperative ORA of all patients was (0.61 ± 0.27) D,in which ＞ 0.75 D were 58 cases (31.9％),and the HORA group was more than the LORA group (P ＜ 0.05).At postoperative 6 months,there was no statistically significant difference in vision acuity between the HORA group (1.06 ± 0.15) and LORA group (1.08 ± 0.15) (t =0.97,P =0.35).There was statistically significant difference in the error ratio between the HORA group (58.11 ± 63.23) ％ and LORA group (26.12 ± 35.37) ％ (t =3.43,P ＜ 0.05).There was statistically significant difference in the correction ratio between the HORA group (146.45 ± 86.63) ％ and LORA group (122.56 ± 36.31) ％ (t =2.81,P ＜ 0.05).Conclusion The error ratio and correction ratio of astigmatic correction by FSLASIK is significantly higher in eyes with high ORA than in eyes with low ORA.Vector analysis should been carried out before the FS-LASIK.

Intensity-modulated radiotherapy planning for nasopharyngeal carcinoma is very complex. The quality of plan is often closely linked to the experience of the treatment planner. In this study, 10 nasopharyngeal carcinoma patients at different stages were enrolled. Based on the scripting of Pinnacle 9. 2 treatment planning system, the computer program was used to set the basic parameters and objective parameters of the plans. At last, the nasopharyngeal carcinoma intensity-modulated radiotherapy plans were completed automatically. Then, the automatical and manual intensity-modulated radiotherapy plans were statistically compared and clinically evaluated. The results showed that there were no significant differences between those two kinds of plans with respect to the dosimetry parameters of most targets and organs at risk. The automatical nasopharyngeal carcinoma intensity-modulated radiotherapy plans can meet the requirements of clinical radiotherapy, significantly reduce planning time, and avoid the influence of human factors such as lack of experience to the quality of plan.
Carcinoma ; Feasibility Studies ; Humans ; Nasopharyngeal Neoplasms ; radiotherapy ; Radiometry ; Radiotherapy Dosage ; Radiotherapy Planning, Computer-Assisted ; Radiotherapy, Intensity-Modulated

The chemical constituents of fistular onion stalk obtained by supercritical CO(2) extraction were separated and purified by silica gel and sephadex LH-20 gel column chromatography and the preparative TLC method and four flavonoids were obtained. On the basis of the spectral data, they were structurally identified as (+)-catechin, (-)-epicatechin, astragalin, and 3-O-beta-D(2-O-beta-D-glucopyranosyl)-glucopyranosides of kaempferol.

BACKGROUND:The effect of advanced glycation end products (AGEs) on bone resorption is controversial. Our previous study has shown that bone resorption is significantly inhibited when AGEs present with pre-osteoclast cells RAW 264.7, while the effect of AGEs on osteoclastic acidification remains unknown. OBJECTIVE:To investigate the effect of AGEs on osteoclastic acidification and the underlying mechanism. METHODS:RAW 264.7 cells were induced by RANKL (15μg/L;normal group) to generate osteoclasts, and AGEs (50-400 mg/L;experimental group) or bovine serum albumin (100 mg/L;control group) were added at the beginning of the induction. The effect of AGEs on bone resorption was evaIuated by anaIyzing the area of bone resorption on the Osteo Assay Surface plates, and the effect of AGEs on osteoclastic acidification was evaluated by acridine orange staining. Furthermore, the expression levels of V-ATPase a3 and CIC-7 were detected to investigate the underlying mechanism. RESULTS AND CONCLUSION:The bone resorption area in the AGEs group was significantly decreased compared with the normal group (P<0.05). Acridine orange staining reveaIed that the red fluorescence (620 nm) intensity in the AGEs group was significantly decreased compared with the normal group (P<0.05), and this inhibitory effect became obvious with the increase of AGEs concentration. Immunocytochemistry, western blot assay and PCR findings showed that the expression levels of V-ATPase a3 and CIC-7 in the AGEs group were decreased significantly compared with the normal group (P<0.05). To conclude, AGEs exert inhibitory effect on osteoclastic acidification, probably by inhibiting the expression of V-ATPase a3 and CIC-7.

Objective To verify the clinical applicability of the published standard intervals of routine clinical chemistry (WS/T404 .1‐2012 ,WS/T404 .2‐2012) based on the health examination results of Han and Uygur populations in Urumqi .Methods This was a retrospective study .The results of serum TP ,ALB ,ALT ,AST ,ALP ,GGT from healthy examination individuals of Han and Uygur populations (from 2013 August to 2015 January) were collected and the healthy cases (age range:20 -79 years old) were chosen to calculate the 2 .5% and 97 .5% percentiles ,excluding the significant abnormal results according to the Medical Deciding Level 2 recommended by Staland .The percents of health cases not falling in the published standard interval were calculated to meet the judgment criterion of verification (<10% ) .Results The test of normality revealed that the Han and Uygur's results of all veri‐fied items were skewed distributions .The 2 .5% and 97 .5% percentiles of the results of two populations were as follows ,TP(Han 65 -81 g/L ;Uygur 64-81 g/L) ,ALB(Han 41-53 g/L ;Uygur 40-52 g/L) ,ALT(Han:male 9-51 U/L and female 7-42 U/L ;Uygur:male 9-53 U/L and female 6-43 U/L) ,AST(Han:male 14-42 U/L and female 12-37 U/L ,Uygur:male 12-42 U/L and female 12-38 U/L) ,ALP(Han:male 45-119 U/L ;Uygur:male 47-122 U/L) ,ALP(female 20-49 years old:Han 35-95 U/L and Uygur 40-104 U/L) ,ALP(female 50-79 years old:Han 43-131 U/L and Uygur 51-132 U/L) ,GGT(Han:male 11-71 U/L and female 8-54 U/L ;Uygur :male 11 -73 U/L and female 7 -55 U/L ) .The percents of AST results for Han's male , Uygur's male and Uygur's female not falling in the published standard reference interval were slightly over 10% ,but AST results o‐ver 10% were mainly under the lower limit of the published standard reference interval .The health case percents for the other veri‐fied items of Han and Uygur populations not falling in the published standard reference interval were under 10% .Conclusion The published standard reference intervals of routine clinical chemistry (WS/T404 .1‐2012 ,WS/T404 .2‐2012) are applicable in our la‐boratory for the detection of Han and Uygur population .

Objective To provide the objective evidence for reducing stat test turnaround time (TAT) reasonably through the comparative analysis of different intervals of stat test TAT between emergency department (ED) and intensive care unit (ICU ) . Methods Laboratory information system was used to collect data about blood cell analysis and biochemical profiles of department of emergency and ICU from 1st January to 31th March ,2014 ,then comparatively analyzing different intervals of stat test TAT be‐tween two departments .Results TAT outlier rates of stat CBC tests ordered by ED and ICU were 2 .4% and 15 .1% ,and that of stat biochemical profiles ordered by ED and ICU were 12 .3% and 24 .5% ,respectively .there were no significant differences in mean times between order‐to‐receipt of stat CBC tests and biochemical profiles ordered by ED and collection‐to‐receipt of stat CBC tests and biochemical profiles ordered by ICU [(11 .2 ± 4 .0) min vs .(11 .2 ± 4 .5) min ,P>0 .05 ;(13 .2 ± 14 .1)min vs .(13 .8 ± 9 .8) min ,P>0 .05] .ED had significantly shorter mean time of receipt‐to‐report than ICU for stat CBC tests and biochemical profile [(5 .8 ± 4 .4) min vs .(19 .3 ± 12 .5) min ,P<0 .01 ;(34 .4 ± 10 .9) min vs .(35 .5 ± 13 .2) min ,P>0 .01] .The TAT mean times of stat CBC tests and biochemical profiles ordered by ED were shorter than those ordered by ICU [(17 .0 ± 6 .2) min vs .(30 .5 ± 14 .9) min ,P<0 .01 ;(46 .9 ± 17 .2) min vs .(49 .3 ± 16 .5) min ,P<0 .01] .Conclusion The ED TATs for CBC tests and biochemical pro‐files are reasonably set ,and each interval of the ED TATs is well controlled .The ICU TATs for CBCs and biochemical profiles should be reset ,and the process of stat test for ICU should be optimized .

The chemical constituents of fistular onion stalk obtained by supercritical CO2 extraction were separated and purified by silica gel and sephadex LH-20 gel column chromatography and the preparative TLC method and four flavonoids were obtained.On the basis of the spectral data,they were structurally identified as(+)-catechin,(-)-epicatechin,astragalin,and 3-O-β-D(2-O-β-D-glucopyranosyl)-glucopyranosides of kaempferol.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.