Foodborne illnesses caused by Salmonella pose significant threats to worldwide public health safety.In this study,a rapid method for screening viable Salmonella in oyster sauce and milk was developed by utilizing an electronic microbial growth analyzer(EMGA).Target food samples were diluted 10-fold with RVS broth and loaded into test tubes.Test tubes were positioned in the EMGA to determine the bacterial growth curves and the time required to reach the maximum growth rate(Tmgr).Using Salmonella typhimurium(S.typhimurium)asan model species,there was linear relationship between the logarithmic value of viable bacterial concentration(lgC)and Tmgr over the range of 5×101-5×106 CFU/mL,with a detection limit of 10 CFU/mL.For oyster sauce,the regression equation was Tmgr(min)=-80.775lg[C/(CFU/mL)]+754.96(R2=0.9907),and the recovery rates of S.typhimurium ranged from 95.2%to 119.8%,with relative standard deviations(RSD)ranging from 3.5%to 16.3%.For milk,the regression equation was Tmgr(min)=-71.922 lg[C/(CFU/mL)]+618.65(R2=0.9985),with recovery rates ranging from 98.4%to 110.6%and RSD ranging from 6.4%to 12.8%.The EMGA method required only one portable instrument,and involving only three manual steps,i.e.,dilution,transfer,and insertion.When S.typhimurium contamination reached 106 CFU/mL,the total time consumption,from the unwrapping of samples to the readout of bacterial concentration,was no more than 7 h.When applied to detection of actual oyster sauce and milk samples,the new method demonstrated strong consistency with plate counting results in positive detection rates.This method was superior to the plate counting method,which was generally considered as a gold standard,in terms of accuracy,precision,simplicity and efficiency,representing a promising alternative for the on-site screening and quantification of viable Salmonella in oyster sauce and milk products.

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.

Applying Chinese medicine (CM) is an important strategy for malignant tumor treatment in China. One of the significant characteristics of CM is to treat diseases based on syndrome differentiation. For Western medicine, it is of important clinical significance to formulate guidelines for the diagnosis and treatment of cancer patients based on the characteristics of disease differentiation. In Chinese clinical practice, the combination of disease differentiation and syndrome differentiation is an important feature for cancer treatment in the past. Currently, molecular profiling and genomic analysis-based precision medicine optimizes the anticancer drug design and holds the greatest success in treating cancer patients. Therefore, we want to know which populations of cancer patients can benefit more from CM treatment if the theory of precision medicine is applied to CM clinical practice. So, we developed a novel diagnostic and therapeutic strategy "disease-syndrome differentiation-genomic profiling-prescriptions" for cancer patients by CM syndrome differentiation and precision medicine. As a result, this strategy has greatly enhanced the anti-tumor efficacy of CM and improved clinical outcomes for cancer patients with some gene mutations. Our idea will hopefully establish a novel approach for the inheritance and innovation of CM.
Antineoplastic Agents ; Drugs, Chinese Herbal/therapeutic use* ; Humans ; Medicine, Chinese Traditional ; Neoplasms/therapy* ; Precision Medicine ; Syndrome

The present study explored the underlying mechanism of Astragali Radix-Curcumae Rhizoma-Paridis Rhizoma(AR-CR-PR) in the treatment of colorectal cancer(CRC) by network pharmacology and molecular docking and animal tests and verified the core targets based on the orthotopic transplantation model in nude mice. The active components of AR-CR-PR were retrieved from databases such as TCMSP. The targets of drugs and the disease were obtained from PubChem, SwissTargetPrediction, TTD, and DrugBank, and the intersection targets were imported into STRING for the analysis of the protein-protein interaction(PPI). Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) analyses were performed through DAVID. AutoDock Vina was used to perform molecular docking and binding ability prediction between the active components and the core targets. The effects of AR-CR-PR on tumor growth, metastasis, and phosphorylation of core target proteins in tumor tissues based on the orthotopic transplantation model in nude mice. As revealed by network pharmacology, AR-CR-PR contained nine core components, such as quercetin, curcumin, and β-ecdysone, and the key targets included protein kinase B(AKT1), mitogen-activated protein kinase 3(MAPK3), MAPK1, and epithelial growth factor receptor(EGFR), which was indicated that the anti-CRC effect of AR-CR-PR was presumedly achieved by regulating tumor cell proliferation, apoptosis, migration, and angiogenesis through PI3 K-AKT, MAPK and other signaling pathways. The results of molecular docking showed that the nine core components had strong binding abilities to AKT1 and MAPK3. The results in vivo showed that AR-CR-PR could reduce the volume of the orthotopic tumor, inhibit liver metastasis, and decrease the phosphorylation of AKT1 and MAPK3 in the CRC model. The mechanism of AR-CR-PR in the intervention of CRC may be related to the activation of PI3 K-AKT and MAPK signaling pathway. This study provides a scientific basis for the clinical application of AR-CR-PR in the treatment of CRC and ideas for modern research on AR-CR-PR.
Animals ; Drugs, Chinese Herbal/pharmacology* ; Mice ; Mice, Nude ; Molecular Docking Simulation ; Neoplasms ; Network Pharmacology ; Rhizome

Objective:To explore the possible mechanism of Astragali Radix-Curcumae Rhizoma （AC） in inhibiting tumor growth in the orthotopic transplantation model of colon cancer in mice. Method:The molecular docking technology was used to predict the intermolecular interaction between the main active components of AC and the pathway target proteins， such as stromal cell-derived factor-1 （SDF-1）， C-X-C motif chemokine receptor 4 （CXCR4）， and nuclear factor kappa-B p65 （NF-κB p65）. The orthotopic transplantation model of CT26.WT colon cancer was established in mice for in vivo experimental verification. Sixty BALB/c male mice were randomly divided into a sham operation group， a model group， a 5-fluorouracil （5-Fu， 30 mg·kg^-1） group，and low- （0.32 g·kg^-1）， medium- （0.64 g·kg^-1）， and high-dose （1.28 g·kg^-1） AC groups， with 10 mice in each group. The sham operation group and the model group received normal saline by gavage. The corresponding drugs were administered by gavage in the 5-Fu group and by intraperitoneal injection in the AC groups. After intervention for 15 days， the tumor in situ was completely stripped， and the colon tissues 5-6 cm in length adjacent to the tumor were taken. The tumor volume was measured and calculated. The pathological changes of tumor tissues and colon tissues were observed by Hematoxylin-Eosin （HE） staining. Western blot was used to detect the protein expression of SDF-1， CXCR4， p-NF-κB p65 in colon tissues. Western blot and Real-time quantitative polymerase chain reaction （Real-time PCR） were used to detect SDF-1， CXCR4， NF-κB p65， Cyclin D₁， oncogene c-Myc protein and mRNA expression in tumor tissues. Result:Compared with the model group， 5-Fu and AC groups showed reduced tumor volumes in situ （P<0.05， P<0.01）， with the tumor inhibition rate in the 5-Fu group as high as （61.38±2.34）%. The tumor-inhibiting effect was optimal in the medium-dose AC group， with the tumor inhibition rate of （43.43±3.71）%. Compared with the model group， 5-Fu and AC groups showed relieved pathological changes of tumor and colon tissues. Specifically， AC down-regulated the protein expression levels of SDF-1， CXCR4， and p-NF-κB p65 in colon tissues （P<0.01）， and down-regulated the protein and mRNA expression levels of SDF-1， CXCR4， NF-κB p65， Cyclin D₁， and c-Myc in tumor tissues （P<0.05， P<0.01）. Conclusion:AC can inhibit the growth of orthotopic transplantation tumor of colon cancer， and its intervention mechanism may be related to the regulation of related protein and mRNA expression in the SDF-1/CXCR4/NF-κB signaling pathway.

OBJECTIVE: To observe the clinical effect of electronic moxibustion on dysphagia in patients with achalasia of cricopharyngeus muscle after stroke. METHODS: Sixty patients with dysphagia of achalasia of cricopharyngeus muscle were randomly divided into an observation group and a control group, 30 cases in each group. One patient in the observation group and 2 cases in the control group dropped off. The patients in the control group were treated with routine medical treatment, acupuncture treatment and swallowing rehabilitation training; the patients in the observation group were additionally treated with electronic moxibustion at Lianquan (CV 23), Tiantu (CV 22), Tianding (LI 17) and Futu (LI 18), 30 min each treatment. Both groups were treated 5 times a week for 4 weeks. The musculoskeletal ultrasound (MSUS) was applied to test the activity of parapharyngeal wall and the dysphagia score of Ichiro Fujishima was compared before and after 4-week treatment. RESULTS: After treatment, the activity of the parapharyngeal wall and the dysphagia score of Ichiro Fujishima were increased in both groups (<0.01, <0.05). The changes of activity of parapharyngeal wall and dysphagia score of Ichiro Fujishima in the observation group were greater than the control group (<0.05, <0.01). CONCLUSION Electronic moxibustion can improve the impaired swallowing function and reconstruct the normal swallowing process.

BACKGROUNDGlobally, the proportion of child deaths that occur in the neonatal period remains a high level of 37-41%. Differences of cause in neonate death exist in different regions as well as in different economic development countries. The specific aim of this study was to investigate the causes, characteristics, and differences of death in neonates during hospitalization in the tertiary Neonatal Intensive Care Unit (NICU) of China.

METHODSAll the dead neonates admitted to 26 NICUs were included between January l, 2011, and December 31, 2011. All the data were collected retrospectively from clinical records by a designed questionnaire. Data collected from each NICU were delivered to the leading institution where the results were analyzed.

RESULTSA total of 744 newborns died during the 1-year survey, accounting for 1.2% of all the neonates admitted to 26 NICUs and 37.6% of all the deaths in children under 5 years of age in these hospitals. Preterm neonate death accounted for 59.3% of all the death. The leading causes of death in preterm and term infants were pulmonary disease and infection, respectively. In early neonate period, pulmonary diseases (56.5%) occupied the largest proportion of preterm deaths while infection (27%) and neurologic diseases (22%) were the two main causes of term deaths. In late neonate period, infection was the leading cause of both preterm and term neonate deaths. About two-thirds of neonate death occurred after medical care withdrawal. Of the cases who might survive if receiving continuing treatment, parents' concern about the long-term outcomes was the main reason of medical care withdrawal.

CONCLUSIONSNeonate death still accounts for a high proportion of all the deaths in children under 5 years of age. Our study showed the majority of neonate death occurred in preterm infants. Cause of death varied with the age of death and gestational age. Accurate and prompt evaluation of the long-term outcomes should be carried out to guide the critical decision.

Cause of Death ; China ; Female ; Hospital Mortality ; Humans ; Infant ; Infant Mortality ; Infant, Newborn ; Infant, Newborn, Diseases ; mortality ; Intensive Care Units, Neonatal ; statistics & numerical data ; Male ; Perinatal Death ; Retrospective Studies