Objective To evaluate the clinical application value of Xpert detection system of Clostridium difficile (C.difficile).Methods A total of 43 stool specimens from the patients with diarrhea were collected,and C.difficile in stool specimens were detected by the Xpert detection system,the toxigenic culture method,and the toxin detection method which detected the toxin of C.difficile by VⅥDAS automatic analyzer after anaerobic culture,respectively.The analytic performance of Xpert detection system was evaluted based on the toxigenic culture method as the gold standard.Meanwhile,the consistency of the results from different detection methods was compared.The ribotype 027 strain (ATCC BAA-1870) simulating the stool specimen was further used to verify the Xpert detection system.Results Based on the gold standard of the toxigenic culture method,the sensitivity,specificity,positive predictive value and negative predictive value of the Xpert detection system were 90.9％,93.8％,83.3％ and 96.8％,respectively.The Kappa values for the consistency between the Xpert detection system and the toxigenic culture method or the toxin detection method were 0.822 (P ＜ 0.05) and 0.419 (P ＜ 0.05),respectively.Moreover,the ribotype 027 strain simulating the stool specimen was verified by the Xpert detection system successfully.Conclusion The Xpert detection system may rapidly and accurately detect the C.difficile in stool specimens,especially the ribotype 027 strain with high toxicity.

Objective To compare the difference in ischemic heart disease (IHD) incidence between left and right breast cancer treated with post-op radiation therapy.Methods We retrospectively reviewed electronic database of breast cancer patients treated in our cancer center from October 2006 to December 2011.Clinical data were recorded including clinical features,radiation fraction,and IHD.Statistical analysis was performed to compare the difference in IHD incidence between left and right breast cancer.Results Age on diagnosis was significantly associated with IHD (P ＜ 0.05).Compare to younger patients (≤60),the increased hazard ratio of IHD in older patients (＞60) was 3.84.The left breast cancer patients had greater incidence of IHD with the increased hazard ratio of 1.57 although this difference did not reach statistical power (P ＞ 0.05).No patients got IHD in the intensity-modulated radiation therapy group.Conclusions Left-side breast cancer patients may have more probability to get IHD after thoracic radiation therapy compared to right-side patients.We recommend that left-side breast cancer patients should be treated with intensity-modulated radiation therapy to spare heart if they receive prophylactic radiation therapy after surgery.

Objective To investigate the resistance status of different integrons of Shigella sonnei (S.sonnei) and to analyze the distribution of resistant genes in integrons in Jiangsu Province.Methods A total of 32 strains of S.sonnei isolated from six cities of Jiangsu Province in 2011 were collected.The antibiotic susceptibility was tested by disk diffusion method.The molecular homology was analyzed by pulsed field gel electrophoresis (PFGE).The detection and classification of integrons were achieved by analyzing the positive polymerase chain reaction (PCR) products using restriction fragment length polymorphism (RFLP).RFLP and DNA sequencing were used to analyze the resistance genes in integrons.Results Multi-drug resistance (MDR) was detected in 28 (87.5％) S.sonnei strains.The resistant rates to ampicillin,nalidixic acid and tetracycline were highest (87.5％,respectively).However,it was sensitive to norfloxacin.PFGE analysis showed that there were 3 kinds of homologous clones involving 31 strains of the 32 S.sonnei strains.Among them,2,5 and 24 strains had the same clones,respectively.Accordingly,they spread within one,two and five different cities.The detection rates of class 1,class 2 and the atypical class 1 integrons in S.sonnei were 62.5％ (20/32),81.3％ (26/32) and 21.9％ (7/32),respectively,and no class 3 integron was detected.Sequence analysis of class 1 integron variable area revealed that it contained multiple resistant genes (aacA4-cmlA1 and dfrA1-aadA 1) ; dfrA1-sat 1-aadA 1 from class 2 integron and blara-30-aadA 1 from atypical class 1 integron were also identified.Conclusions In 2011,homologous S.sonnei strains spread among different cities in Jiangsu Province.MDR strains are prevalent and integrons are widespread which mediated the emergence of MDR strains.

Objective To investigate the pathogen distribution and susceptibility profile of fungal isolates from bloodstream infections,and valuate the clinical utility of G test in diagnosis of fungal infections for the purpose to improve antifungal therapy.Methods A retrospective analysis was carried out to analyze the fungal pathogens isolated from bloodstream infections in the First Affiliated Hospital of Nanjing Medical University during the period from January 2013 through December 2015 and their antimicrobial susceptibility.Results A total of 114 fungal strains were isolated from bloodstream infections during the 3-year period,most of which were Candida (99/114,86.8％),especially Candida albicans (30.7％).About 41.2％ (47/114) of the fungal strains were isolated from Department of Thoracic Surgery (10,5 and 4 strains in 2013,2014 and 2015),Hematology (11 strains in 2014),and ICU (7 strains in 2014).Antimicrobial susceptibility testing showed that all the fungal strains (100％) were susceptible to amphotericin B,but 83.5％ susceptible to itraconazole (the lowest).G test was positive before the result of blood culture in 13 of the 54 patients who received G test.Conclusions Candida was the most common fungus in fungal bloodstream infection.Amphotericin B is the most active antifungal agent in vitro.Blood culture combined with serological test can provide clinicians an earlier and reliable diagnosis.

AIM: To clone EBV-LMP2A gene, construct and identify the recombinant retroviral vector and stable cell strains expressing EBV LMP2A. METHODS: The full-length EBV LMP2A gene was generated by RT-PCR amplification from B95.8 cells which contain complement nucleotide sequence of EBV LMP2A gene. The gene was ligated to T-vector and sequenced to construct retroviral vector consisting with LMP2A. To produce retroviral virus, packing cells, 293T cells were co-transfected with recombinant retroviral expression vector pGEZ-LMP2A and two auxiliary viral vectors pHIT456 and pHIT60 by lipofectAMINE2000. Viral titration was performed according to the instructions of the manufacturer. To establish L929 cell line stable expressing LMP2A, L929 cells were infected with recombinant retrovirus three times and selected by Zeocine. The Zeocine-resistant clones (L929/LMP2A) were screened for LMP2A expression by RT-PCR and Western blot. RESULTS: The recombinant retrovirus vector carrying LMP2A gene was constructed successfully. Transfection yield a titer of 5×10~8 infectious particles/L. The infected L929 cells were selected by Zeocine. Results of RT-PCR and Western blot indicated that L929 transgenetic cells could stably express EBV-LMP2A. CONCLUSION: The L929 cell line stably expressing LMP2A provides suitability for extraction of the LMP2A protein and preparations of the vaccine for the therapy of EBV-associated diseases.

Autophagy extensively exists in eukaryotes, which utilizes lysosomes to degrade the damaged organelles or proteins, maintain the stability of the intracellular environment and provide energy. It can also participate in the growth, proliferation and apoptosis of tumor cells through autophagy-related genes and signaling pathways. Radiotherapy is one of the main treatments for cancer, whereas tumor cells often have radiation resistance, which reduces the clinical efficacy. Previous studies have demonstrated that autophagy is associated with the radiosensitivity of tumor cells, but the conclusions are different. In this article, different effects of autophagy upon the radiosensitity of tumor cells were reviewed.

OBJECTIVE: To detect the levels of Epstein-Barr virus (EBV) latent membrane protein 1 Antibodies (LMP1-Ab) in nasopharyngeal carcinoma (NPC)sera and discuss the clinical significance of this test in diagnosis, prognosis, and immune-targeted therapy of NPC. METHOD: Enzyme-linked immunosorbent assay (ELISA) and Western blot method were used to detect the LMP1-Ab levels in 61 NPC sera, 30 nasopharyngitis sera, and 55 normal sera. The relationship between the LMP1-Ab level and clinical and pathological features of NPC was analyzed. RESULT: ELISA test showed that LMP1 antibodies level was significantly higher in nasopharyngeal carcinoma group than those in nasopharyngitis group and in healthy group and there were statistical significances (all P<0.05). In SNPC group, the LMP1-Ab level was not related to the pathological grade and cervical lymph node metastases (P>0.05). Western blot test revealed that the expression of LMP1 antibodies was higher in NPC sera than in nasopharyngitis sera and in normal sera. CONCLUSION LMP1-Ab level was higher in nasopharyngeal carcinoma group than in nasopharyngitis group and in normal group. Therefore, LMP1 may be considered as a tumor correlated antigen to help the diagnosis and immune-targeted therapy of NPC.
Adolescent ; Adult ; Aged ; Antibodies, Viral ; blood ; Carcinoma ; Case-Control Studies ; Enzyme-Linked Immunosorbent Assay ; Female ; Herpesvirus 4, Human ; immunology ; Humans ; Male ; Middle Aged ; Nasopharyngeal Carcinoma ; Nasopharyngeal Neoplasms ; blood ; pathology ; Viral Matrix Proteins ; immunology ; Young Adult

Infectious diseases are one of the major threats to global public health. Inconvenience of diagnosis and treatment frequently causes misdiagnosis, missing diagnosis or overtreatment, resulting in serious clinical outcomes. As an important branch of artificial intelligence, machine learning has been widely used in multiple fields. Predictive models created based on patients’ clinical characteristics, laboratory tests, and imaging examinations are effective for prediction and evaluation of clinical diagnosis, therapeutic efficacy and prognosis, as well as detection of outbreaks. Machine learning modeling has the advantages of high efficiency, high accuracy and interpretability as compared to traditional modeling approaches, which provides a new tool for diagnosis and treatment of infectious diseases. This review summarizes the advances of applications of machine learning in clinical predictive models for infectious diseases.