Objective To report clinical and laboratory features of a rare case who was primary myelofibrosis (PMF) with positive JAK2 V617F terminating in T-acute lymphoblastic leukemia (T-ALL).Methods A rare case of PMF terminating in ALL was found, the quantity and quality of JAK2 gene mutation were defined by PCR methods, collected the clinical dates. Results The JAK2 V617F gene mutations were all positive pre and post-blast, the mutant rates respectively were 71.21% and 83.56 %. The interval from PMF to leukemia was 22 months, and from leukemia to death was 27 days. Conclusion PMF with positive JAK2 V617F terminating in ALL is a rare case, clinical prognosis is poor and survival time is short.

[ ABSTRACT] AIM:To investigate the role of hydrogen sulfide ( H2 S) on impaired wound healing in ob/ob mice and the underlying mechanism.METHODS:The ob/ob mice were randomly divided into 3 groups, including vehicle, in-sulin and NaHS for treatment.C57BL/6 mice were treated with vehicle as control.Full-thickness punch biopsy wounds were created on the mice.Firstly, H2 S concentrations in the skins and granulation tissues were measured.The mRNA ex-pression of cystathionineγ-lyase ( CSE) was detected by RT-qPCR.The protein expression of CSE and MMP-9 were deter-mined by Western blot.The neutrophil and monocyte/macrophage infiltration was analyzed by immunohistochemistry me-thod.The levels of tumor necrosis factor (TNF)-αand interleukin (IL)-6 were measured by ELISA.Collagen formation was measured by Masson staining.RESULTS:The H2 S levels in the skin and granulation were significantly decreased in ob/ob mice and increased in the NaHS-treated mice ( P<0.05 ) .CSE expression at mRNA and protein levels was significantly decreased in ob/ob mice compared with the control mice (P<0.05).The wound healing period was significantly shorter in NaHS group than that in vehicle-treated ob/ob mice group (P<0.05), in which the insulin group had no difference with vehicle ob/ob mice group.The neutrophil and monocyte/macrophage infiltration, and TNF-αand IL-6 levels were signifi-cantly increased in ob/ob groups, but were decreased in NaHS group ( P<0.01 or P<0.05 ) .Meanwhile, NaHS in-creased collagen formation in the granulation tissues of ob/ob mice.CONCLUSION:H2 S/CSE down-regulation contributes
to impaired wound healing in diabetes, which is alleviated by exogenous H2 S possibly through anti-inflammation.

Objective To summarize the etiology,diagnosis and treatment of three cases of duodenal perforation. Methods The data of 3 cases of children with duodenal perforation in our hospital from September 14,2016 to June 20,2017 were retrospectively analyzed. The causes,clinical features and treatment of children's duodenal perforation were summarized. Results A total of 2 males and 1 females aged 2 years,3 years and 5 years were included in the 3 cases. All 3 cases had fever history of upper respiratory tract infection before onset. Acute abdominal pain occurred after oral administration of ibuprofen several times,and all the abdominal plain films prompted pneumoperitoneum. Three cases of perforation sites were duodenal anterior wall,diameter were 0. 5-1 cm. Two cases of small amount of pneumoperitoneum were explored and repaired the duodenal perforation by 3D laparoscopic,1 case underwent laparotomy to repair the duodenal perforation due to a large number of liquid pneumoperitoneum and severe shock. Repair of 3 cases were covered with omentum. Three cases were all cured without anastomotic fistula, ulcer, adhesive intestinal obstruction or other complications. Followed-up in the department of gastroenterology,3 cases had no Helico-bacter pylori infection. Conclusion Repeatedly oral administration of ibuprofen can cause duodenal perfora-tion in children in the short term. Once the digestive tract perforation confirmed,emergency surgical explora-tion is needed. Laparoscopic repair of duodenum perforation is safe and effective and may have a faster recov-ery. We can choose exploratory laparotomy if conditions are not allowed.

ObjectiveTo establish a more accurate and sensitive liquid chromatography-ultraviolet (LC-UV) method for the determination of uric acid in rat serum, and compare the results with those of commercial kits, providing a new method for the accurate determination of uric acid in the rat hyperuricemia model induced by potassium oxonate.Methods A hyperuricemia model was established by intraperitoneal injection of potassium oxonate (300 mg/kg) into SPF-grade male SD rats, and the control group was administered an equal amount of 0.5% sodium carboxymethylcellulose solution. Blood samples were collected from the posterior orbital venous plexus and centrifuged to obtain serum samples. After precipitation with 0.1% trifluoroacetic acid-acetonitrile (containing the internal standard 3,4-dihydroxybenzylamine hydrobromide), the supernatant was injected for analysis. Uric acid was separated on a Waters XBridge HILIC column (150 mm×4.6 mm, 3.5 μm) using acetonitrile (containing 0.5% formic acid and 2 mmol/mL ammonium formate) as the organic phase and methanol solution (methanol∶water=1∶1, containing 0.5% formic acid with 2 mmol/L ammonium formate) as the aqueous phase for isocratic elution and detection at 290 nm. Serum samples treated with activated carbon were used as substitute matrices for the methodological verification. Serum uric acid levels in rats with potassium oxonate-induced hyperuricemia were measured using the established LC-UV method and commercially available kits (uricase and phosphotungstic acid methods), and the accuracies of the three methods were compared.Results Serum uric acid showed a good linear relationship (R>0.999) at mass concentration of 10–200 μg/mL in rats, the lower limit of quantification was 10 μg/mL, the accuracy ranged from -2.17% to 2.21%, the intra-batch precision ranged from 0.52% to 1.95%, the inter-batch precision ranged from 3.04% to 4.90%, and the extraction recovery ranged from 83.12% to 89.91%. In the rat model, the results obtained using the commercially available phosphotungstic acid method kit were significantly higher than those of the LC-UV method, and those obtained using the commercially available uricase method kit were significantly lower than those of the LC-UV method, but the LC-UV method showed the best recovery of the spiked sample (95.90%–99.96%).ConclusionThe LC-UV method developed in this study can determine the concentration of uric acid in rat serum with higher accuracy than commercially available kits and is recommended for the determination of serum uric acid in the rat model of hyperuricemia induced by potassium oxonate.

Objective To quantitatively analyze the risk indicators of re-introduction of imported malaria in China and their weighting coefficients, so as to investigate the difference in the contribution of risk indicators included in the current risk assessment framework for re-introduction of imported malaria in China to the risk assessment of re-introduction of imported malaria. Methods Publications pertaining to the risk assessment framework for re-introduction of imported malaria in China that reported the risk indicators and their weighting coefficients were retrieved in PubMed, Web of Science, CNKI, Wanfang Data, and VIP with terms of “malaria”, “re-introduction/re-transmission/re-establishment”, “risk assessment/risk evaluation/risk prediction” from the inception of the database through 3 August 2023, and literature search was performed in Google Scholar to ensure the comprehensiveness of the retrieval. Basic characteristics of included studies were extracted using pre-designed information extraction forms by two investigators, and data pertaining to risk indicators of re-introduction of imported malaria were cross-checked by these two investigators. The risk indicators included in the risk assessment framework for re-introduction of imported malaria in China and their weighting coefficients were visualized with the Nightingale’s rose diagrams using the software R 4.2.1, and the importance of risk indictors was evaluated with the frequency of risk indicators included in the risk assessment framework and the ranking of weighting coefficients of risk indicators. In addition, the capability of risk indicators screened by different weighting methods was compared by calculating the ratio of the maximum to the minimum of the weighting coefficients of the risk indicators screened by different weighting methods. Results A total of 2 138 publications were retrieved, and following removal of duplications and screening, a total of 8 publications were included in the final analysis. In these 8 studies, 8 risk assessment frameworks for re-introduction of imported malaria in China and 52 risk indicators of re-introduction of imported malaria were reported, in which number of imported malaria cases (n = 8) and species of malaria vectors were more frequently included in the risk assessment frameworks (n = 8), followed by species of imported malaria parasites (n = 6) and population density of local malaria vectors (n = 6), and species of local malaria vectors (n = 6), number of imported malaria cases (n = 5) and species of imported malaria parasites had the three highest weighting coefficients (n = 4). The weighting methods included expert scoring method, combination of expert scoring method and analytic hierarchy process, and combination of expert scoring method and entropy weight method in these 8 studies, and the ratios of the maximum to the minimum of the weighting coefficients of the risk indicators screened by the expert scoring method were 1.143 to 2.241, while the ratios of the maximum to the minimum of the weighting coefficients of the risk indicators screened by combination of the expert scoring method and analytic hierarchy process were 34.970 to 162.000. Conclusions Number of imported malaria cases, species of imported malaria parasites, species of local malaria vectors and population density of local malaria vectors are core indicators in the current risk assessment framework for re-introduction of imported malaria in China. Combination of the expert scoring method and analytic hierarchy process is superior to the expert scoring method alone for weighting the risk indicators.

Objective To create risk predictive models of healthcare-seeking delay among imported malaria patients in Jiangsu Province based on machine learning algorithms, so as to provide insights into early identification of imported malaria cases in Jiangsu Province. Methods Case investigation, first symptoms and time of initial diagnosis of imported malaria patients in Jiangsu Province in 2019 were captured from Infectious Disease Report Information Management System and Parasitic Disease Prevention and Control Information Management System of Chinese Center for Disease Control and Prevention. The risk predictive models of healthcare-seeking delay among imported malaria patients were created with the back propagation (BP) neural network model, logistic regression model, random forest model and Bayesian model using thirteen factors as independent variables, including occupation, species of malaria parasite, main clinical manifestations, presence of complications, severity of disease, age, duration of residing abroad, frequency of malaria parasite infections abroad, incubation period, level of institution at initial diagnosis, country of origin, number of individuals travelling with patients and way to go abroad, and time of healthcare-seeking delay as a dependent variable. Logistic regression model was visualized using a nomogram, and the nomogram was evaluated using calibration curves. In addition, the efficiency of the four models for prediction of risk of healthcare-seeking delay among imported malaria patients was evaluated using the area under curve (AUC) of receiver operating characteristic curve (ROC). The importance of each characteristic was quantified and attributed by using SHAP to examine the positive and negative effects of the value of each characteristic on the predictive efficiency. Results A total of 244 imported malaria patients were enrolled, including 100 cases (40.98%) with the duration from onset of first symptoms to time of initial diagnosis that exceeded 24 hours. Logistic regression analysis identified a history of malaria parasite infection [odds ratio (OR) = 3.075, 95% confidential interval (CI): (1.597, 5.923)], long incubation period [OR = 1.010, 95% CI: (1.001, 1.018)] and seeking healthcare in provincial or municipal medical facilities [OR = 12.550, 95% CI: (1.158, 135.963)] as risk factors for delay in seeking healthcare among imported malaria cases. BP neural network modeling showed that duration of residing abroad, incubation period and age posed great impacts on delay in healthcare-seek among imported malaria patients. Random forest modeling showed that the top five factors with the greatest impact on healthcare-seeking delay included main clinical manifestations, the way to go abroad, incubation period, duration of residing abroad and age among imported malaria patients, and Bayesian modeling revealed that the top five factors affecting healthcare-seeking delay among imported malaria patients included level of institutions at initial diagnosis, age, country of origin, history of malaria parasite infection and individuals travelling with imported malaria patients. ROC curve analysis showed higher overall performance of the BP neural network model and the logistic regression model for prediction of the risk of healthcare-seeking delay among imported malaria patients (Z = 2.700 to 4.641, all P values < 0.01), with no statistically significant difference in the AUC among four models (Z = 1.209, P > 0.05). The sensitivity (71.00%) and Youden index (43.92%) of the logistic regression model was higher than those of the BP neural network (63.00% and 36.61%, respectively), and the specificity of the BP neural network model (73.61%) was higher than that of the logistic regression model (72.92%). Conclusions Imported malaria cases with long duration of residing abroad, a history of malaria parasite infection, long incubation period, advanced age and seeking healthcare in provincial or municipal medical institutions have a high likelihood of delay in healthcare-seeking in Jiangsu Province. The models created based on the logistic regression and BP neural network show a high efficiency for prediction of the risk of healthcare-seeking among imported malaria patients in Jiangsu Province, which may provide insights into health management of imported malaria patients.