Objective To investigate the diagnosis and treatment procedures of primary colonic malignant lymphoma(PCML). Methods Data of clinical and pathological findings, surgical treatment and prognosis of 12 cases with PCML verified by pathology were retrospectively analyzed, workups of barium clysma,colon-scopic examination and multislice spiral computed tomography(MSCT) were compared to evaluate their role in diagnosis. Results The classic presentation of PCML included abdominal pain, abdominal bulge, bowel obstruction, gastrointestinal bleeding, and serum levels of tumor markers were within the normal ran-ges. Six cases underwent procedure of barium clysma, and anomaly appeared in 2 cases, however, there were no indications of lymphoma, 6 cases underwent colon-scopic examination, anomaly in 3 cases, of which 1 revealed possibility of lymphoma, 10 cases underwent MSCT; 9 cases demonstrated tumor origin by CT scan of which diagnosis was established in 5 cases. All the patients underwent surgery. No incidence of peri-opreative death happened. Non-Hodgkin' s lymphoma was confirmed in all of cases. For all of the cases a T-cell origin was in 1 case and a B-cell origin in other cases. Ten cases were administrated postoperative chem-otherapy. 11 cases were followed up, and the overall 1-year and 3-year survival rates were 81.9% (9/11) and 54.5% (6/11), respectively. Conclusions Typical presentation is still lacking for PCML, workups of barium clysma and colon-seopic examination are little sensitive and specific to make the diagnosis. However, MSCT is useful in diagnosing PCML with its characteristic information as well as clinical findings. Surgical management and postoperative adjuvant-chemotherapy would be likely the optimal therapeutic maneuver of this disease in early period.

To investigate the angiotensin I-converting enzyme (ACE) inhibitory activity of beta-chain hemoglobin fragments, 17 fragments were synthesized by microwave-assisted solid-phase synthesis method. Wang resin or Trt(2-Cl) resin, Fmoc and HBTU-HOBt were used as solid carrier, N-terminal amino acid protecting groups and coupling reagents, respectively. The ACE inhibitory, alpha-glucosidase inhibitory, antibacterial and antitumor activities of the synthesized fragments were assayed. In vitro, Val-Val-Tyr-Pro-Trp-Thr showed high ACE inhibitory activity (IC50 = 7.42 micromol x L(-1)). The results indicate that there are two active sites in Val-Val-Tyr-Pro-Trp-Thr-Gln-Arg-Phe, one consists of Val-Val-, and the other -Gln-Arg-Phe. Peptides showed high ACE inhibitory activity when the N-terminal was hydrophobic amino acid such as Val and C-terminal tripeptide contained Phe, Trp or Arg. Some of the fragments showed low a-glucosidase inhibitory activity. No antibacterial activity or antitumor activity was detected in vitro. The results indicate that these peptides have a potential antihypertensive effect and possible application in the treatment of hypertension.

The purpose of this study is to develop glipizide push-pull osmotic pump (PPOP) tablets by using a formulation design expert system and an artificial neural network (ANN). Firstly, the expert system for the formulation design of osmotic pump of poor water-soluble drug was employed to design the formulation of glipizide PPOP, taking the dissolution test results of Glucotrol XL as the goal. Then glipizide PPOP was prepared according to the designed formulations and the in vitro dissolution was carried out. And in vivo evaluation was carried out between the samples which were similar to Glucotrol XL and the Glucotrol XL in Beagle dogs. The range of the factors of formulation and procedure, which could influence the drug release, was optimized using artificial neural network. Finally, the design space was found. It was found that the target formulation which was similar to Glucotrol XL in dissolution test could be obtained in a short period by using the expert system. The samples which were similar to Glucotrol XL were bio-equivalent to the Glucotrol XL in Beagle dogs. The design space of the key parameter coating weight gain was 9.5%-12.0%. It could be concluded that a well controlled product of glipizide PPOP was developed since the dissolution test standard of our product was more strict than that of Glucotrol XL.

Traditional sleep scoring system describes the sleep EEG characterized by features in time domain as well as frequency domain. Power Spectral Density (PSD) is one of the well-used methods to observe the occurrence of specified rhythms. However, the parameter model based PSD estimation is used with the assumption that the model order is determined as low as possible through prior knowledge. This paper briefs the development of Autoregressive Model Order (ARMO) criterion, and provides the distribution of ARMOs for specified sleep EEG, which shows that ARMOs concentrate on several well separated regions that are indicative of the microstructure and transition states. This study suggests the promising perspective of ARMO as a special EEG feature for weighing complexity, randomness and rhythm components.
Delta Rhythm ; Electroencephalography ; Humans ; Models, Neurological ; Regression Analysis ; Signal Processing, Computer-Assisted ; Sleep Stages ; physiology

Objective To investigate the antitumor effect of the recombined adeno-associated virus encoding caveolin-1 regulated by progression-elevated gene (PEG) promotor on the angiogenesis of implanted human hepatocellular carcinoma(HCC) cell lines in a nude mouse model. Methods HepG2 cells were inoculated subcutaneously into NOD/SCID mice, and animals were treated with rAAV-PEG-caveolin-1 after tumor cell innoculation. The fluorescence ratio of Evans blue to FITC-dextran was used to assess the changes of microvasculature permeability of the tumor. Western blot and immunohistochemical analyses were employed to detect PECAM-1 expression in tumor microvascular endothelium and microvessel density(MVD), respectively; NOS activity was assessed by citrulline generation. Tumor growth was observed and tumor cell apoptosis in tumor tissues were measured by TUNEL. Results Tumor growth was significantly inhibited in mice injected with rAAV-PEG-caveolin-1. The administration of rAAV-PEG-caveolin-1 significantly blocked vascular leakage in the tumor microcirculation. The levels of PECAM-1 protein detected by Western blot were markedly reduced in rAAV-PEG-caveolin-1-treated mice, and there were fewer MVD in tumors from caveolin-1-treated mice, while NOS catalytic activity was much lower in rAAV-PEG-caveolin-1-treated mice compared to the control and empty vector-treated animals. TUNEL demonstrated significant induction of tumor cell specific apoptosis. Conclusions rAAV-PEG-caveolin-1 can reduce tumor progression through blocking microvascular formation by inhibiting eNOS.

Objective To investigate the impairment and the effect factors of encoding of episodic memory in patients with cerebral infarction. Methods 112 cases cerebral infarction patients and 115 healthy elders as controls were tested for episodic memory encoding with episodic pictures accomplished in computer, and compare the differences of encoding of episodic memory between the two groups. Results The remember indexes ( REM )of encoding memory test in patient group was significantly lower than that in control group( (70.81 ± 6.08 )vs (84.67 ± 4.49), P ＜ 0.01 ). The REM in patients with different impaired areas was significantly different ( (65.88 ± 5.73 ), (68.92 ± 4.65 ), (73.39 ± 6.20), ( 73.53 ± 3.44), P ＜ 0. 01 ). The REM in frontal lobe infarction group was significantly lower than that in temporal lobe infarction group (P ＜ 0.05 ), and in temporal lobe infarction group was significantly lower than that in basal ganglia infarction group and corona radiate infarction group (P＜0.05, P＜0. 01). The REM in cortex infarction group was significantly lower than that in under cortex group ( ( 67.37 ± 5.40 ), ( 73.46 ± 4.99 ), P ＜ 0.01 ). The REM in small cerebral infarction group was significantly higher than that in large cerebral infarction group( (72.67 ±4.47 ), (67.56 ± 6.18 ), P＜0.01 ). The size of cerebral infarction diameter was related with the REM( r= -0.39, P＜0. 01 ). The REM among control group,infarction with atrophy group, and infarction without atrophy group were significantly different( (67.03 ± 6. 17 ),( 72.84 ± 5. 00 ), ( 84.67 ± 4.49 ), P ＜ 0. 01 ). The REM in infarction with atrophy group was significantly lower than that in infarction without atrophy group and control group( both P＜0.01 ) ,The REM in infarction without atrophy group was significantly lower than that in control group (P ＜ 0.01). Conclusion The encoding of episodic memory was impaired in cerebral infarction patients. The infarction parts,size of infarction area and atrophy was related with the impairment of encoding of episodic memory.

Objective To collect the demographic,lifestyle and clinical factors of patients with cerebrovascular disease,and analyze the vascular cognitive impairment(VCI) factors and set up high-risk factors model.methods 505 patients with cerebrovascular disease hospitalization in department of geriatrics and neurology in hospital from October 2014 to October 2016 were enrolled.According to the questionaire survey data of demographics,lifestyle and clinical factors,the patients were divided into training set (421 cases) and test set (84 cases),and training set were divided into the non-VCI set (225 cases) and VCI set (196 cases).Analyzed the influence factors of VCI in patients with cerebrovascular disease by decision tree algorithm,and compared it with the Logistic regression analysis and chi-square and established the decision tree model for risk factors of VCI.Result sAccording to the VCI decision tree model,cross validation model recognition accuracy was 73.63%,while test set prediction accuracy was 73.81%.Alcoholism,hobbies,education level,tea drinking,diabetes,hypertension,diet,age,sleep and physical exercise were classification of node variables,while drinking was the root.The probability of VCI had significant difference (P<0.05) in the crowds with different risk factors.According to Result s of Logistic regression analysis,education level,drinking,exercise and diabetes were independent risk factors for VCI,while the model prediction accuracy was 66.98%,and test set prediction accuracy was 53.57%.According to the ROC curve of the decision tree model and the Logistic regression model,the decision tree model AUC was 0.737 (95%CI 0.688 to 0.786),and the Logistic regression model AUC was 0.664 (95%CI 0.612 to 0.717).Conclusion It is suggested that the decision tree model might be superior to logistic regression model in the prediction accuracy for VCI of patients with cerebrovascular disease.The alcoholism,diabetes,high blood pressure,high fat diet and insomnia are risk factors of VCI,while hobbies,high level of education,physical exercise and drinking tea can be the protective factors of the VCI.

This paper is devoted to predicting the transmembrane helices in proteins by statistical modeling. A novel segment-training algorithm for Hidden Markov modeling based on the biological characters of transmembrane proteins has been introduced into training and predicting the topological characters of transmembrane helices such as location and orientation. Compared to the standard Balm-Welch training algorithm, this algorithm has lower complexity while prediction performance is better than or at least comparable to other existing methods. With a 10-fold cross-validation test on a database containing 160 transmembrane proteins, an HMM model trained with this algorithm outperformed two other prediction methods: TMHMM and MEMSTAT; the novel method was validated by its prediction sensitivity (97.0%) and correct location (91.3%). The results showed that this algorithm is an efficient and a reasonable supplement to modeling and prediction of transmembrane helices.
Algorithms ; Data Interpretation, Statistical ; Mathematical Computing ; Membrane Proteins ; chemistry ; Models, Statistical ; Protein Conformation

Residues in protein sequences can be classified into two (exposed / buried) or three (exposed/intermediate/buried) states according to their relative solvent accessibility. Markov chain model (MCM) had been adopted for statistical modeling and prediction. Different orders of MCM and classification thresholds were explored to find the best parameters. Prediction results for two different data sets and different cut-off thresholds were evaluated and compared with some existing methods, such as neural network, information theory and support vector machine. The best prediction accuracies achieved by the MCM method were 78.9% for the two-state prediction problem and 67.7% for the three-state prediction problem, respectively. A comprehensive comparison for all these results shows that the prediction accuracy and the correlative coefficient of the MCM method are better than or comparable to those obtained by the other prediction methods. At the same time, the advantage of this method is the lower computation complexity and better time-consuming performance.
Algorithms ; Computational Biology ; methods ; Databases, Protein ; Markov Chains ; Models, Chemical ; Models, Molecular ; Proteins ; chemistry ; classification ; Sequence Analysis, Protein ; methods ; Solubility

Correct sleep scoring is the base of sleep studying; nonlinear features of EEG can represent different sleep stages. In this paper, correlation dimension (D2) and approximate entropy (ApEn) of sleep EEG have been calculated. The statistical results reveal that: D2 does not come to be saturated when the embedding dimension increases, but the relative value of D2 can effectively distinguish different sleep stages. ApEn has the advantage of calculating simply, steady result and representing preferably different sleep stages. ApEn and the relative value of D2 reveal, from different point of view, the same rule about EEG (brain) complexity changing, that is, both complexity and its fluctuation are maximal in the subject's awake hour, are decreasing with the deepening of sleep, but the complexity in REM is about the level between S1 and S2.
Electroencephalography ; Entropy ; Humans ; Nonlinear Dynamics ; Sleep ; physiology ; Sleep Stages ; physiology