Objective To establish an improved hemisection model of spinal cord injury(SCI)in rats with less severe injury and increased sur-vival rate. Methods Female Sprague-Dawley rats(n=20)were randomly divided into 2 groups:standard and improved hemisection model of SCI. Basso-Beattie-Bresnahan(BBB)scores were carried out to determine the hindlimb locomotor function at 1 d,3 d,1 week and 2 weeks post SCI,respectively. In addition,duration of operation,blood loss,location of posterior midline,and success rate of spinal cord exposure during the second surgery were used as the main parameters to evaluate the significance of the new model. Results Compared with the standard hemisection model,the improved hemisection model of SCI exhibited shorter duration of operation,less blood loss,higher BBB score,more accurate location of posterior midline,and higher success rate of spinal cord exposure during the second surgery. Based on the improved hemisection model of SCI, transplantation model of scar tissue in spine cord was then successfully constructed with a success rate above 70%. Conclusion The improved hemisection model of SCI shows significant advantages in many aspects related to the operation,which is applicable to the study of SCI,especially the non-acute SCI.

Objective To evaluate the validity and reliability of multi-slice spiral CT (MSCT) in preoperative TNM staging judgment of rectal carcinoma. Methods Three hundred and one patients with rectal carcinoma were diagnosed and treated consecutively in Colorectal and Anal Surgery Department of Shanxi Province Tumor Hospital from January 2009 to December 2009. The clinical data of these patients were analyzed retrospectively. The diagnosis results were compared between the preoperative MSCT staging and the postoperative pathological staging,the ROC curve and the diagnostic concordance test were analyzed by software Medcalc 11.2. Results The sensitivity, specificity, Kappa value, area under the curve of TNM staging were 64.7% ,96. 8% ,0. 667,0. 808 for T2 staging tumors; 93.8% ,75.0% ,0.709,0.844 for T3 staging tumors;87. 8% ,98. 1% ,0. 859,0. 929 for T4 staging tumors; 72. 0% ,91.2% ,0. 619,0. 816 for N staging tumors;92. 7%, 99. 7%, 0. 925,0. 963 for M staging tumors respectively. Conclusion The diagnostic value of independent use of MSCT in estimating the infiltration degree and lymph node metastasis of rectal cancer is very poor and cannot be used in preoperative staging judgment.

Objective To clone the coding region and 3′non?coding region of calmodulin 2(CaM2)in guinea pig,to provide the genetic informa?tion for studying the gene function of Calmodulin 2. Methods Total RNA was extracted from heart tissue of guinea pig,the coding region and 3′non?coding region of CaM2 were amplified by RT?PCR and 3′?RACE PCR methods,and the recombinant plasmid was constructed by inserting cDNA of the coding region and 3′non?coding region of CaM2 into the cloning vector by genetic engineering technology followed by DNA sequencing and se?quence analysis. Results The cloned coding region of CaM2 was 450 bp,and the 3′non?coding region of CaM2 was 660 bp. The amino acid se?quences of the coding region of CaM2 was consistent with those of other CaM subtypes,and the 3′non?coding region of CaM2 had low homology with those of other subtypes. Conclusion The cloning of CaM2 coding region and 3′non?coding region in guinea pig was the foundation for further study on the gene function of CaM2 and its role in related diseases.

Objective To explore whether dithiothreitol(DTT)is helpful for PreScission Protease to cut off the GST from GST?CT3 protein. Meth?ods The pGEX?6P?3/CT3 recombinant plasmid was transfected into Escherichia coli BL21,and the GST?CT3 fusion protein was purified by B?PER method. PreScission Protease was applied with 10 mmol/L DTT to cut off the GST,then the SDS?PAGE was performed for identification of the CT3 protein. Results Without DTT,it was very difficult for PreScission Protease to cut off the GST from GST?CT3 protein. However,in the pres?ence of 10 mmol/L DTT,PreScission Protease could cut off the GST easily as identified by SDS?PAGE. Conclusion 10 mmol/L DTT can help Pre?Scission Protease to cut GST from GST?CT3 protein,so as to achieve high concentration of CT3.

Objective To investigate the role of Calcineurin binding protein 1(Cabin1)in renal tubular epithelial cells(RTECs)injury. Methods The male Sprague-Dawley rats were randomly divided into Sham-oper-ated and 5/6 nephrectomized group. Nephrectomized rats were further divided into two groups ,which were 4 and 8 weeks after operation,including 6 rats in each group. Rats were sacrificed at 4 or 8 weeks after nephrectomy,then control or remnant kidneys were harvested. 2μm sections of kidney tissues were collected and stained with Masson's trichrome and were graded for tubulointerstitial lesion score (TILS). RTECs mitochondrial morphology changes were detected by electron microscope. Western blot was applied to detect Cabin1 protein level in the renal tissue. Results At 8 weeks after the operation,plenty of RTECs fell off from the basement membrane,accompanied with interstitial fibrosis and the infiltration of inflammatory cells. Moreover ,TILS were significantly increased in rats at 8 weeks after operation while compared to sham-operated rats(7.16 ± 0.52 vs. 0.00 ± 0.00,P<0.05). RTECs mi-tochondria begun to swell at 4 weeks after 5/6 nephrectomy,while the disruption of cristae could be found in rats at 8 weeks. Cabin1 protein expression apparently increased in the remnant kidney. Cabin1 protein obviously increased in rats at 8 weeks after the surgery compared to sham-operated rats(0.97 ± 0.09 vs. 0.22 ± 0.07,P<0.05)and rats at 4 weeks after nephrectomy(0.97 ± 0.09 vs. 0.45 ± 0.03,P<0.05). Conclusions Cabin1 is overexpressed during RTECs injury in 5/6 nephrectomized rats. It can be a crucial factor regulating the damage of RTECs.

Objective With the focus on emerging infectious diseases and diseases of unknown cause,the study aims to realize multi-point trigger monitoring of infectious diseases through key monitoring sites and key populations.Methods Using ar-tificial intelligence,deep learning,big data and other information technologies to build an intelligent information center for infec-tious diseases with patients'disease files as the core,construct a core capacity of infectious disease surveillance,early warning and situation prediction,and predict and evaluate the importance of infectious disease warning signals.Results The system cov-ered 1 425 primary-level medical institutions,18 hospitals,2 580+schools,4 134 pharmacies,4 laboratories and civil affairs departments,detected 55 kinds of infectious diseases and 6 kinds of syndrome monitoring signals.Since its launch,121 000 ac-tive notification cards have been issued,more than 54 000 new notification cards have been added,35.256 million times of multi-source monitoring and 14.4 million disease files have been recorded.Conclusion By expanding monitoring content and chan-nels,we realized early monitoring,auxiliary investigation and multi-mode visual early warning of infectious diseases,built a multi-point trigger mechanism,and moved forward the infectious disease surveillance.

Objective To construct a recombinant plasmid vector containing the distal fragment of the distal C-terminus (dDCT) of the Cav 1.2 channel,and express,extract,and purify dDCT protein and characterize its biological activity.Methods dDCT cDNA was ligated into the pGEX-6p-1 vector to create a recombinant plasmid that was subsequently transformed into Escherichia coli BL21 competent cells.Expression of GST-dDCT fusion protein from this plasmid was induced with isopropy-β-D-thiogalactoside,and the resulting protein was purified using glutathione-sepharose 4B beads.The biological activity of dDCT was analyzed by GST pull-down assay.Results The recombinant plasmid was verified by restriction enzyme digestion and sequencing.The concentration and purity of the dDCT protein,which was extracted by ultrasonication,were high enough to detect dDCT activity.The binding of dDCT to CT1 was determined to be concentration-dependent.Conclusion The recombinant dDCT plasmid was successfully constructed,providing the fundamental basis for future studies on mechanisms of Cav 1.2 channel autoregulation.

Objective:Postdoctoral researchers in Chinese universities commonly face a high risk of mental health issues,such as depression,yet the underlying causes and mechanisms remain unclear.This study aims to explore the influence of childhood socioeconomic status(SES)on depression among postdoctoral researchers and the mediating roles of current subjective SES and perceived stress in this process. Methods:An online survey was conducted among postdoctoral researchers at a university.The survey included a general information questionnaire,the Childhood Socioeconomic Status Scale,the Subjective Socioeconomic Status Scale,the Perceived Stress Scale,and the Patient Health Questionnaire.A total of 505 valid responses were collected.Pearson correlation analysis was used to analyze the data,and the PROCESS macro was employed for chain mediation analysis. Results:Childhood SES was significantly positively correlated with current subjective SES(P<0.05)and significantly negatively correlated with postdoctoral tenure,perceived stress,and depression(all P<0.05).Current subjective SES was significantly negatively correlated with perceived stress and depression(both P<0.05),while perceived stress was significantly positively correlated with depression(P<0.05).The chain mediation effect of childhood SES → current subjective SES → perceived stress → depression was significant(P<0.05). Conclusion:Childhood socioeconomic status can influence depression among postdoctoral researchers through the mediating roles of current subjective socioeconomic status and perceived stress.These findings provide a target for the prevention and intervention of depression in postdoctoral populations and offer a reference for the development of mental health promotion strategies for young university faculty.

Objective:To analyze the antibody levels and dynamic changes in patients infected with 2019-novel coronavirus(2019-nCoV).Methods:The average age of 72 corona virus disease 2019 (COVID-19) patients was (45.53±16.74)years(median age:47 year), including (44.88±17.09) years(median age:46 year) for 38 males and (46.32±16.52)years (median age:46 year) for 34 females in Loudi City, Hunan Province. There is no significant difference in genders between the severe and mild groups (χ2=0.916, P>0.05). There is a significant difference in the age between the severe and mild groups ( F=3.315, P<0.05). The blood samples of 72 discharged patients were collected and the consistence of IgM and IgG antibodies were detected by chemiluminescence method. SPSS25.0 was used for gender, age, case type and antibody analysis of variance, χ 2 test and other analysis. Results:The average time of the serum samples collection of 72 patients was (34.89±9.02)days (median time: 34 days) from onset of COVID-19, and (14.53±8.35) days (median time: 14 days) from discharge. The positive rate of IgM or IgG was 97.22% (70/72), and the positive rate of IgM and IgG was 48.61% (35/72) and 97.22% (70/72) respectively. Serum COVID-19 antibodies were detected in 72 patients from 1st to 40th days after discharge. The average concentration of IgM in 1-7 days, 8-14 days, 15-21 days, 22-28 days, above 29 days were 21.91(7.07-52.84)AU/ml, 14.16(6.19-32.88)AU/ml, 11.36(6.65-42.15)AU/ml, 8.15(3.66-30.12)AU/ml, 2.98(0.46-6.37)AU/ml. There was no significant difference in the time of IgM antibody concentration ( H= 8.439, P>0.05). The average concentrations of IgG in 1-7 days, 8-14 days, 15-21 days, 22-28 days, 29 days and above were 169.90 (92.06-190.91) AU/ml, 163.89 (91.19-208.02) AU/ml, 173.31 (95.06-191.28) AU/ml, 122.84 (103.19-188.34) AU/ml, 101.98 (43.75-175.30) AU/ml, respectively, ( H=2.232, P>0.05). The IgM becomes negative after the 3rd week of discharge and decreases rapidly with time. The IgG concentration higher than IgM during the same period, and keep at high level without any change, and decrease in the fourth week. Among them, 5 cases developed "re-infection" within 1-3 weeks after discharge, and the rate of "re-infection" was 6.94% (5/72 cases). Conclusions:After the COVID-19 patients are discharged from the hospital, the level of antibodies produced varies greatly among individuals, but the overall changes in antibodies have a certain pattern. It is recommended to strengthen the antibody monitoring during hospitalization and after discharge from the hospital to reduce the "re-infection" rate and potential risk of infection.

Objective:To analyze the antibody levels and dynamic changes in patients infected with 2019-novel coronavirus(2019-nCoV).Methods:The average age of 72 corona virus disease 2019 (COVID-19) patients was (45.53±16.74)years(median age:47 year), including (44.88±17.09) years(median age:46 year) for 38 males and (46.32±16.52)years (median age:46 year) for 34 females in Loudi City, Hunan Province. There is no significant difference in genders between the severe and mild groups (χ2=0.916, P>0.05). There is a significant difference in the age between the severe and mild groups ( F=3.315, P<0.05). The blood samples of 72 discharged patients were collected and the consistence of IgM and IgG antibodies were detected by chemiluminescence method. SPSS25.0 was used for gender, age, case type and antibody analysis of variance, χ 2 test and other analysis. Results:The average time of the serum samples collection of 72 patients was (34.89±9.02)days (median time: 34 days) from onset of COVID-19, and (14.53±8.35) days (median time: 14 days) from discharge. The positive rate of IgM or IgG was 97.22% (70/72), and the positive rate of IgM and IgG was 48.61% (35/72) and 97.22% (70/72) respectively. Serum COVID-19 antibodies were detected in 72 patients from 1st to 40th days after discharge. The average concentration of IgM in 1-7 days, 8-14 days, 15-21 days, 22-28 days, above 29 days were 21.91(7.07-52.84)AU/ml, 14.16(6.19-32.88)AU/ml, 11.36(6.65-42.15)AU/ml, 8.15(3.66-30.12)AU/ml, 2.98(0.46-6.37)AU/ml. There was no significant difference in the time of IgM antibody concentration ( H= 8.439, P>0.05). The average concentrations of IgG in 1-7 days, 8-14 days, 15-21 days, 22-28 days, 29 days and above were 169.90 (92.06-190.91) AU/ml, 163.89 (91.19-208.02) AU/ml, 173.31 (95.06-191.28) AU/ml, 122.84 (103.19-188.34) AU/ml, 101.98 (43.75-175.30) AU/ml, respectively, ( H=2.232, P>0.05). The IgM becomes negative after the 3rd week of discharge and decreases rapidly with time. The IgG concentration higher than IgM during the same period, and keep at high level without any change, and decrease in the fourth week. Among them, 5 cases developed "re-infection" within 1-3 weeks after discharge, and the rate of "re-infection" was 6.94% (5/72 cases). Conclusions:After the COVID-19 patients are discharged from the hospital, the level of antibodies produced varies greatly among individuals, but the overall changes in antibodies have a certain pattern. It is recommended to strengthen the antibody monitoring during hospitalization and after discharge from the hospital to reduce the "re-infection" rate and potential risk of infection.