Objective To explore fecal bacteria transplantation for the treatment of severe gastrointestinal disease caused by food allergy. Method The therapeutic process of fecal bacteria transplantation for treatment of severe food allergy gastrointestinal disease was retrospectively analyzed, and the related literature was reviewed. Results A 2-year-old boy had onset of intestinal infection and diarrhea was persistent even though he had received adequate anti-infection therapy and supportive treatment. Finally, the patient received the treatment of fecal bacteria transplantation and the symptoms were then improved. No adverse reactions were observed in 2 months of follow-up. In foreign literature, fecal bacteria transplantation in children is mainly applied to clostridium difficile infection (CDI) and inflammatory bowel disease (IBD), with efficiency of 90%- 100% and 55.6% - 100%, respectively. While in the domestic literature, fecal bacteria transplantation in children is mainly used in CDI and antibiotic associated diarrhea, and the effective rate is 100%. No serious adverse reactions were found in all the researches. Conclusion Fecal transplantation is safe and effective in the treatment of children with severe gastrointestinal disease caused by food allergy, but its application in children is not yet mature and needs more in-depth researches.

Objective To explore the characteristics of emotional memory in adolescent with anxiety disorders.Methods Totally 40 adolescent patients with anxiety disorders who met the DSM-5 diagnostic criteria were selected as the anxiety disorder group,40 normal adolescents matched with anxiety disorder group in terms of gender,age and education level served as the control group.All subjects of the two groups were implemented by emotional memory test task.Results (1) In emotional memory test,the negative picture score of adolescent anxiety disorder group(2.10±0.75)was significantly lower than that of control group (2.76±0.92) (t=-3.29,P＜0.05).There were no significant difference in positive and neutral picture scores between the two groups(P＞0.05).(2)Compared with control group,the positive picture,neutral picture and total recognition accuracy of adolescent anxiety disorder group both were significantly decreased ((0.24±0.09) vs (0.33±0.08),(0.22±0.10) vs (0.32±0.14),(0.25±0.08) vs (0.33±0.09)) (t=-4.28,-4.28,-3.85,all P＜0.05).There was no significant difference in negative picture recognition accuracy between the two groups (P＞0.05).In adolescent anxiety disorder group,there were significant differences in the correct recognition rates of negative pictures,positive pictures and neutral pictures in anxiety disorder group (F=3.39,P＜0.05),while there was no significant difference in the control group (F=0.04,P＞0.05).(3) The positive picture recognition accuracy and total recognition accuracy in adolescent anxiety disorder group were negatively correlated with Hamilton Anxiety Scale (HAMA) (F=0.04,P＜ 0.05).Conclusion Adolescent anxiety disorders exist in emotional memory defects,and its positive emotional memory deficit is negatively correlated with the severity of anxiety.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

OBJECTIVETo analyze the clinical characteristics of Mycoplasma pneumoniae-associated hemophagocytic syndrome (MP-HLH).

METHODA retrospective investigation of the clinical manifestation, laboratory test, imagelogy, clinical course and outcome of 3 cases with MP-HLH seen between June 2013 and July 2013 in Shenzhen Children's Hospital, and review of relevant literature were conducted.

RESULTOf the 3 cases of MP-HLH, 2 were males, one was female, the ages were 1 year, 3 years and 6 years, respectively. They had no underlying disease previously. All the 3 cases had onset of fever, cough as main symptoms. Diagnosis of refractory Mycoplasma pneumoniae pneumonia was made, which was accompanied by decreased neutrophils [(0.08-0.68)×10(9)/L], hemoglobin [(79-103) g/L], platelet [(64-157)×10(9)/L], plasma fibrinogen [(1.3-1.5) g/L], lactate dehydrogenase [(1,170-1,285) U/L] and increased serum ferritin [(936.7-39 789.0) µg/L] in the third week of course. In two cases the T lymphocytes decreased, and the NK cell activity decreased significantly in one. Bone marrow cytology showed prompted bone marrow hyperplasia, and the phenomenon of phagocytosed blood cells. CT scan was performed for all the cases and consolidation with pleural effusion were shown. Two cases were admitted to PICU, and required endotracheal intubation and mechanical ventilation. Flexible bronchoscopy and bronchial lavage were performed and bronchial cast was found in two cases. All of them were treated with macrolide combined with other antibiotics, glucocorticoids and gamma globulin combination therapy, including one case given dexamethasone [10 mg/(m2·d)], cyclosporine[6 mg/(kg·d)], etoposide [150 mg/(m2·d)] chemotherapy. Two cases were cured, and 1 case died. The authors summarized the 18 cases reported in domestic and foreign literature. Foreign children were diagnosed and treated with steroids in 1-2 weeks, and 10 cases were cured, and 2 cases died. They died of massive hemorrhage and meningoencephalitis, and domestic children were diagnosed and treated within two to 4 weeks after onset, 5 cases were cured, one case died of severe pneumonia.

CONCLUSIONMP-HLH is a rare disease in children, and had acute onset, rapid progression and high mortality. Early treatment with steroids was associated with a good prognosis, the key to successful treatment is early diagnosis and treatment, avoiding the immune cascade. Too late a diagnosis or development of serious complications may lead to death.

Anti-Bacterial Agents ; therapeutic use ; Bronchoalveolar Lavage Fluid ; Bronchoscopy ; Child ; Child, Preschool ; Fatal Outcome ; Female ; Fever ; Glucocorticoids ; therapeutic use ; Humans ; Infant ; Lymphohistiocytosis, Hemophagocytic ; diagnosis ; drug therapy ; microbiology ; Macrolides ; therapeutic use ; Male ; Mycoplasma pneumoniae ; isolation & purification ; Pleural Effusion ; Pneumonia, Mycoplasma ; complications ; diagnosis ; drug therapy ; Respiration, Artificial ; Retrospective Studies ; Tomography, X-Ray Computed ; Treatment Outcome