Immune response analysis of solid organ transplantation recipients inoculated with inactivated COVID-19 vaccine: A retrospective analysis.

Objective: This study aimed to evaluate the efficacy and safety of solid organ transplantation recipients inoculated with an inactivated COVID-19 vaccine. Methods: We retrospectively analyzed the antibody levels and related adverse events of non-transplantation subjects and solid organ transplant recipients, both pre-transplantation (individuals awaiting organ transplantation) and post-transplantation (individuals who have undergone organ transplantation), who received inactivated COVID-19 vaccines from February 2021 to July 2022. Results: The study included 38 pre-transplantation vaccination group, 129 post-transplantation vaccination group, and 246 non-transplantation group. The antibody titer was assessed monthly within the period of 1-12 months after the last injection. The antibody-positive rate among the three groups were 36.84, 20.30, 61.17% (P < 0.05). The antibody-positive rates among three groups with one, two doses vaccine were not significantly different (P > 0.05), but were significantly different after three doses (P < 0.05). The antibody titers among three groups were significantly different after two doses (P < 0.05). Adverse reactions occurred in six transplant recipients, which were relieved after treatment, and not in the non-transplantation subjects. Conclusion: Inactivated COVID-19 vaccine is safe and effective for solid organ transplantation recipients, at least two doses of which should be completed before organ transplant surgery.

Comparison of different preoperative objective nutritional indices for evaluating 30-d mortality and complications after liver transplantation.

BACKGROUND: The nutritional status is closely related to the prognosis of liver transplant recipients, but few studies have reported the role of preoperative objective nutritional indices in predicting liver transplant outcomes. AIM: To compare the predictive value of various preoperative objective nutritional indicators for determining 30-d mortality and complications following liver transplantation (LT). METHODS: A retrospective analysis was conducted on 162 recipients who underwent LT at our institution from December 2019 to June 2022. RESULTS: This study identified several independent risk factors associated with 30-d mortality, including blood loss, the prognostic nutritional index (PNI), the nutritional risk index (NRI), and the control nutritional status. The 30-d mortality rate was 8.6%. Blood loss, the NRI, and the PNI were found to be independent risk factors for the occurrence of severe postoperative complications. The NRI achieved the highest prediction values for 30-d mortality [area under the curve (AUC) = 0.861, P < 0.001] and severe complications (AUC = 0.643, P = 0.011). Compared to those in the high NRI group, the low patients in the NRI group had lower preoperative body mass index and prealbumin and albumin levels, as well as higher alanine aminotransferase and total bilirubin levels, Model for End-stage Liver Disease scores and prothrombin time (P < 0.05). Furthermore, the group with a low NRI exhibited significantly greater incidences of intraabdominal bleeding, primary graft nonfunction, and mortality. CONCLUSION: The NRI has good predictive value for 30-d mortality and severe complications following LT. The NRI could be an effective tool for transplant surgeons to evaluate perioperative nutritional risk and develop relevant nutritional therapy.

Improved Bayesian Optimization Framework for Inverse Thermal Conductivity Based on Transient Plane Source Method.

In order to reduce the errors caused by the idealization of the conventional analytical model in the transient planar source (TPS) method, a finite element model that more closely represents the actual heat transfer process was constructed. The average error of the established model was controlled at below 1%, which was a significantly better result than for the analytical model, which had an average error of about 5%. Based on probabilistic optimization and heuristic optimization algorithms, an optimization model of the inverse heat transfer problem with partial thermal conductivity differential equation constraints was constructed. A Bayesian optimization algorithm with an adaptive initial population (BOAAIP) was proposed by analyzing the influencing factors of the Bayesian optimization algorithm upon inversion. The improved Bayesian optimization algorithm is not affected by the range and individuals of the initial population, and thus has better adaptability and stability. To further verify its superiority, the Bayesian optimization algorithm was compared with the genetic algorithm. The results show that the inversion accuracy of the two algorithms is around 3% when the thermal conductivity of the material is below 100 Wm-1K-1, and the calculation speed of the improved Bayesian optimization algorithm is three to four times faster than that of the genetic algorithm.

In vitro and vivo study of tranilast protects from acute respiratory distress syndrome and early pulmonary fibrosis induced by smoke inhalation.

BACKGROUND: Tranilast (N-[3＇,4＇-dimethoxycinnamoyl]-anthranilic acid) is an analog of a tryptophan metabolite. It was identified with anti-inflammatory and antifibrotic activities, and used in the treatment of a variety of diseases, such as anti - allergy, bronchial asthma, and hypertrophic scars. As a drug with few adverse reactions, tranilast has attracted great attention, but its application is limited due to the uncertainty of dosages and mechanisms. In this study, the protection effects of different doses of tranilast on smoke inhalation mediated lung injury on rats, and on the damage of three kinds of lung cells in vitro were investigated. METHOD: In vivo, Sprague-Dawley rats were randomly divided into sham group, smoke group (rats were exposed to pine sawdust smoke three times, each time for 5 min), different doses of tranilast treatment group (doses were 100 mg/kg, 200 mg/kg and 300 mg/kg, ip.) and placebo group. After 1, 3 and 7 days, pulmonary function, pathologic injury by HE staining, cytokines and oxidative stress level by kits were determined. At 7days, lung fibrosis was assessed by Masson's trichrome staining and the level of hydroxyproline (HYP). In vitro, three kinds of lung cells from normal rats were isolated: type II alveolar epithelial cells (AT-II), pulmonary microvascular endothelial cells (PMVECs) and pulmonary fibroblasts (PFs). To investigate the potential effects of tranilast on cell proliferation, cell cycle and cytokine production of three kinds of lung cells exposed to smoke. RESULTS: Compared with smoke group and placebo group, tranilast treatment significantly reduced histopathological changes (such as pulmonary hemorrhage, edema and inflammatory cell infiltration, etc.), significantly reduced histopathological score (p < 0.05), increased arterial oxygen partial pressure, and decreased the levels of IL-1ß, TNF-α, TGF-ß1 (p < 0.05), oxidative stress and the expression of nuclear transcription factor κB (NF-κB) smoke exposed rats (p < 0.01). In particular, the effect of 200 mg/kg dose was more prominent. In vitro, smoke induced AT-II and PMVECs apoptosis, improved PFs proliferation (p < 0.01), activity of SOD and decreased the content of MDA (p < 0.01). However, tranilast seems to be turning this trend well. The inflammatory factor IL-11ß, TNF-α and TGF-ß1, and the expression of NF-κB were significantly lower in the tranilast treatment than in the smoke group (p < 0.01). CONCLUSION: This study indicates that tranilast had a protective effect on acute respiratory distress syndrome and early pulmonary fibrosis of rats in vivo. In addition, tranilast promotes proliferation of AT-II and PMVECs but inhibits PFs proliferation, down-regulates secretion of inflammatory cytokines and alleviates oxidative stress of AT-II, PMVECs and PFs after smoke stimuli in vitro.

The upregulation of CLGN in hepatocellular carcinoma is potentially regulated by hsa-miR-194-3p and associated with patient progression.

Background: Patients with hepatocellular carcinoma (HCC) have poor prognosis, especially in advanced stages. Targeted therapy is the main treatment for advanced HCC patients, but the optimal targets for HCC remain poorly understood. The main purpose of this study was to identify potential novel prognostic markers and therapeutic targets. Methods: Firstly, differentially expressed genes (DEGs) in HCC were identified from the Gene Expression Omnibus (GEO) database. The expression, significance in prognosis, and potential mechanisms of DEGs were analyzed using GEPIA, TIMER, HPA, Kaplan Meier Plotter, CBioPortal, miRWalk, TargetScan, and ENCORI databases. Immunohistochemical staining was used to determine the protein expression levels of potential candidate genes. Results: The mRNA levels of MND1, STXBP6, and CLGN were significantly increased in HCC (p< 0.01). HCC patients with elevated CLGN mRNA levels had poorer overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), and disease-specific survival (DSS) (p < 0.05). Higher MND1 mRNA levels significantly correlated with poorer DFS in HCC patients (p< 0.05). However, there was no significant correlation between STXBP6 expression and prognosis of HCC (p> 0.05). Further analysis revealed that patients with elevated CLGN mRNA expression in advanced pathology stages had poorer prognosis (p< 0.01). In addition, CLGN protein levels were elevated in HCC compared to their levels in normal tissues. The mRNA levels of CLGN had no significant correlation with the abundance of six common tumor infiltrating lymphocytes in HCC (COR < 0.5). Moreover, the mutation rate of CLGN was less than 1% in HCC patients (10/1089). Finally, the expression level of hsa-miR-194-3p in HCC was significantly lower than that in normal tissues (p < 0.05), and prognosis of HCC with low expression of hsa-miR-194 was poor (p < 0.05). Conclusion: The upregulation of CLGN in HCC is significantly associated with poor patient prognosis, especially in the advanced stages, and may be regulated by hsa-miR-194-3p. These findings suggest that CLGN may be closely related to the progression of HCC, and is a potential therapeutic target and prognostic indicator for patients with advanced HCC.

Efficacy and safety of transarterial chemoembolization plus sorafenib in patients with recurrent hepatocellular carcinoma after liver transplantation.

Objectives: To explore the benefit and safety of transarterial chemoembolization (TACE) in combination with sorafenib in patients with recurrent hepatocellular carcinoma (HCC) after orthotopic liver transplantation (OLT). Methods: In this multi-center retrospective study, 106 patients with recurrent HCC after OLT were included. Fifty-two patients were treated with TACE plus sorafenib (TS group) and 54 were treated with TACE alone (TC group). Primary and secondary endpoints including overall survival (OS) and progression-free survival (PFS), and safety were assessed. Results: The median OS (17 vs 10 months, P=0.035) and PFS (12 vs 6 months, P=0.004) in the TS group were longer than those in the TC group. On multivariate analysis, BCLC stage (HR [hazard ratio]=0.73 [95% CI, 0.27-0.99], P=0.036) and sorafenib medication (HR=2.26 [95% CI, 1.35-3.69], P=0.01) were identified as independent prognostic risk factors for OS. No severe adverse events related to sorafenib were noted in the TS group. Four patients discontinued sorafenib due to intolerance. Conclusion: TACE in combination with sorafenib is a feasible regimen to improve the survival with mild toxicity in patients with recurrent HCC after OLT.

Risk Score Based on Two microRNAs as a Prognostic Marker of Hepatocellular Carcinoma and the Corresponding Competitive Endogenous RNA Network.

PURPOSE: Liver transplantation (LT) currently yields the best outcomes for hepatocellular carcinoma (HCC). However, tumor recurrence still occurs in some patients. Identifying markers that predict HCC recurrence after LT is an unmet medical need. METHODS: In this study, differential expression analysis was used to identify differentially expressed microRNAs (DEmiRs) between HCC and liver tissues in the The Cancer Genome Atlas database and in data from patients with recurrent or non-recurrent HCC in the GSE64989 dataset. The expression profiles of the overlap DEmiRs were used to construct an miRNA-based risk score to predict prognosis using Cox regression analysis. The target genes of the miRNAs of interest were predicted, and they were analyzed for functional enrichment. Furthermore, we used the miRNAs of interest to construct a competitive endogenous RNA (ceRNA) network of long non-coding RNAs (lncRNAs), miRs and mRNAs. RESULTS: Four up-regulated and three down-regulated miRNAs in HCC and recurrent HCC after LT were considered as candidate miRs. MiR-3200-3p and miR-3690 were selected to construct the miR-based risk score, which was found to be associated with poor overall survival and progression-free survival. Furthermore, it proved to be an independent prognostic factor after adjusting for other clinicopathological factors. The corresponding ceRNA networks of these two miRs that we constructed may help to understand their regulatory mechanisms in HCC. CONCLUSION: We propose a risk score based on miR-3200-3p and miR-3690 that may be useful as a prognostic marker to predict HCC recurrence after LT. We generated a ceRNA network involving these miRNAs, which may help reveal their regulatory roles in HCC.

Correlationship between Ki67, VEGF, and p53 and Hepatocellular Carcinoma Recurrence in Liver Transplant Patients.

BACKGROUND AND AIMS: Patients with hepatocellular carcinoma (HCC) who undergo orthotopic liver transplantation (OLT) are at risk for posttransplant tumor recurrence. The aim of this study was to evaluate the correlation between the expression of Ki67, VEGF, and p53 in HCC and clinicopathological characteristics of HCC patients, as well as their predictive value for HCC recurrence after OLT. METHODS: 60 patients who underwent OLT and were found to have HCC in the liver explant. The expression of Ki67, VEGF, and p53 in HCC was detected by immunohistochemistry. RESULTS: Ki67 was associated with the tumor number and the grade of differentiation at baseline. VEGF was associated with the diameter and number of tumors, tumor differentiation, and lymph node metastasis. p53 was associated with the tumor diameter and tumor encapsulation. The expression of Ki67, VEGF, and p53 in HCC was correlated with the tumor recurrence after OLT, respectively. Among them, VEGF was an independent predictor for tumor recurrence after OLT. CONCLUSION: Ki67, VEGF, and p53 are associated with the recurrence of HCC after OLT. VEGF independently predicts the recurrence of HCC.

Synergistic removal of particles, SO2, and NO2 in desulfurized flue gas during condensation.

The synergistic removal of multi-pollutants, including particles, SO2, and NO2, is a key concern in the process of flue gas purification, during which the supersaturated environment is an essential premise for the nucleation and deep reduction of particles. The condensation of desulfurized flue gas using heat exchangers can not only recover condensed water and latent heat but also create supersaturated environment to promote the flue gas purification. In this study, an experimental system for desulfurized flue gas condensation is established. The effect and associated mechanism of condensation process on the removal of multi-pollutions are clarified. The results show that particles with an aerodynamic diameter larger than 2.5 µm accounts for 50% in mass proportion. The flue gas temperature drop has positive influence to the increase of the ideal supersaturation degree, which is beneficial for the removal of particles (especially when the aerodynamic diameter is less than 1 µm), SO2, and NO2. The ideal supersaturation degree slightly reduces with the rise of inlet flue gas temperature, which can promote the removal efficiency of small particles, while weaken that of large particles, SO2, and NO2. Caused by the increase of flue gas flow rate, the nucleation process weakens, reducing the removal efficiency of all pollutants (particles, 45.2-28.3%; SO2, 27.5-14.5%; NO2, 21.5-15%). On the whole, the increase of the ideal supersaturation degree contributes to the synergistic removal of pollutants especially particles with smaller radius in the flue gas. The reduction of particles with aerodynamic diameter less than 1 µm is conductive to the synergistic removal of SO2 and NO2.

Comparing the Potential of Near- and Mid-Infrared Spectroscopy in Determining the Freshness of Strawberry Powder from Freshly Available and Stored Strawberry.

The quality of strawberry powder depends on the freshness of the fruit that produces the powder. Therefore, identifying whether the strawberry powder is made from freshly available, short-term stored, or long-term stored strawberries is important to provide consumers with quality-assured strawberry powder. Nevertheless, such identification is difficult by naked eyes, as the powder colours are very close. In this work, based on the measurement of near-infrared (NIR) spectroscopy and mid-infrared (MIR) spectra of strawberry powered, good classification results of 100.00% correct rates to distinguish whether the strawberry powder was made from freshly available or stored fruit was obtained. Furthermore, partial least squares regression and least squares support vector machines (LS-SVM) models were established based on NIR, MIR, and combination of NIR and MIR data with full variables or optimal variables of strawberry powder to predict the storage days of strawberries that produced the powder. Optimal variables were selected by successive projections algorithm (SPA), uninformation variable elimination, and competitive adaptive reweighted sampling, respectively. The best model was determined as the SPA-LS-SVM model based on MIR spectra, which had the residual prediction deviation (RPD) value of 11.198 and the absolute difference between root-mean-square error of calibration and prediction (AB_RMSE) value of 0.505. The results of this work confirmed the feasibility of using NIR and MIR spectroscopic techniques for rapid identification of strawberry powder made from freshly available and stored strawberry.

Human amnion-derived mesenchymal stem cells alleviate lung injury induced by white smoke inhalation in rats.

BACKGROUND: White smoke inhalation (WSI) is an uncommon but potentially deadly cause of acute lung injury and acute respiratory distress syndrome for which no effective pharmaceutical treatment has been developed. This study aimed to determine the protective effects of human amnion-derived mesenchymal stem cells (hAMSCs) against WSI-induced lung injury in rats. METHODS: hAMSCs were injected into rats via the tail vein 4 h after WSI. At 1, 3, 7, 14, and 28 days after cell injection, hAMSCs labeled with PKH26 in lung, heart, liver, and kidney tissues were observed by fluorescence microscopy. The lung injury score was determined by hematoxylin and eosin staining. Lung fibrosis was assessed by Masson's trichrome staining. The computed tomography (CT) score was assessed by CT scanning. The wet/dry weight ratio was calculated. The levels of interleukin (IL)-1ß, IL-6, and IL-10 were determined by enzyme-linked immunosorbent assays. The expression of surfactant protein (SP)-A, SP-C, and SP-D was measured by Western blotting. RESULTS: The injected hAMSCs were primarily distributed in the lung tissues in WSI-induced rats. Compared with the model and phosphate-buffered saline (PBS) group, hAMSC treatment led to reduced lung injury, lung fibrosis, CT score, and inflammation levels in WSI-induced mice. hAMSC treatment also resulted in increased cell retention in the lung, partial pressure of oxygen (PaO2), and PaO2/fraction of inspired oxygen (FiO2) levels, and pulmonary SP-A, SP-C, and SP-D expression compared with that in the model and PBS group. CONCLUSIONS: hAMSCs are a potential cell-based therapy for WSI-induced lung injury.

NO x reduction by CO over ASC catalysts in a simulated rotary reactor: effect of CO2, H2O and SO2.

The influence of CO2, H2O and SO2 on the NO reduction by CO over Fe/Co activated semi-coke catalyst was investigated in a simulated rotary reactor. The results showed that, in the simulated rotary reactor, the influence of CO2 and H2O on the NO adsorption was significant at low temperatures, and the inhibition became weak when increasing the temperature. However, the NO adsorption efficiency could not be improved by increasing temperature after catalyst sulfur poisoning. The heavily inhibited NO adsorption process, which was due to the competitive adsorption and formation of the sulfate, resulted in a low NO reduction efficiency in the presence of CO2, H2O or SO2. The in situ DRIFT study showed that the dominant effect of CO2, H2O and SO2 on the NO adsorption was the inhibition of the free nitrate ions formation. In addition, the introduction of CO2, H2O and SO2 could not change the route of NO reduction, but just reduced the degree of the NO + CO reduction.

Outcomes of liver transplantation for end-stage biliary disease: A comparative study with end-stage liver disease.

AIM: To evaluate the outcomes of patients with end-stage biliary disease (ESBD) who underwent liver transplantation, to define the concept of ESBD, the criteria for patient selection and the optimal operation for decision-making. METHODS: Between June 2002 and June 2014, 43 patients with ESBD from two Chinese organ transplantation centres were evaluated for liver transplantation. The causes of liver disease were primary biliary cirrhosis (n = 8), cholelithiasis (n = 8), congenital biliary atresia (n = 2), graft-related cholangiopathy (n = 18), Caroli's disease (n = 2), iatrogenic bile duct injury (n = 2), primary sclerosing cholangitis (n = 1), intrahepatic bile duct paucity (n = 1) and Alagille's syndrome (n = 1). The patients with ESBD were compared with an end-stage liver disease (ESLD) case control group during the same period, and the potential prognostic values of multiple demographic and clinical variables were assessed. The examined variables included recipient age, sex, pre-transplant clinical status, pre-transplant laboratory values, operation condition and postoperative complications, as well as patient and allograft survival rates. Survival analysis was performed using Kaplan-Meier curves, and the rates were compared using log-rank tests. All variables identified by univariate analysis with P values < 0.100 were subjected to multivariate analysis. A Cox proportional hazard regression model was used to determine the effect of the study variables on outcomes in the study group. RESULTS: Patients in the ESBD group had lower model for end-stage liver disease (MELD)/paediatric end-stage liver disease (PELD) scores and a higher frequency of previous abdominal surgery compared to patients in the ESLD group (19.2 ± 6.6 vs 22.0 ± 6.5, P = 0.023 and 1.8 ± 1.3 vs 0.1 ± 0.2, P = 0.000). Moreover, the operation time and the time spent in intensive care were significantly higher in the ESBD group than in the ESLD group (527.4 ± 98.8 vs 443.0 ± 101.0, P = 0.000, and 12.74 ± 6.6 vs 10.0 ± 7.5, P = 0.000). The patient survival rate in the ESBD group was not significantly different from that of the ESBD group at 1, 3 and 5 years (ESBD: 90.7%, 88.4%, 79.4% vs ESLD: 84.9%, 80.92%, 79.0%, χ(2) = 0.194, P = 0.660). The graft-survival rates were also similar between the two groups at 1, 3 and 5 years (ESBD: 90.7%, 85.2%, 72.7% vs ESLD: 84.9%, 81.0%, 77.5%, χ(2) = 0.003, P = 0.958). Univariate analysis identified MELD/PELD score (HR = 1.213, 95%CI: 1.081-1.362, P = 0.001) and bleeding volume (HR = 0.103, 95%CI: 0.020-0.538, P = 0.007) as significant factors affecting the outcomes of patients in the ESBD group. However, multivariate analysis revealed that MELD/PELD score (HR = 1.132, 95%CI: 1.005-1.275, P = 0.041) was the only negative factor that was associated with short survival time. CONCLUSION: MELD/PELD criteria do not adequately measure the clinical characteristics and staging of ESBD. The allocation system based on MELD/PELD criteria should be re-evaluated for patients with ESBD.

[Clinical application of precise liver surgery techniques for donor hepatectomy in living donor liver transplantation].

OBJECTIVE: To evaluate the effect of techniques of precise liver surgery for donor hepatectomy in living donor liver transplantation. METHODS: Eighty-nine donors aged from 19 to 57 years were performed by the same surgical team from June 2006 to December 2013 in Chinese People's Liberation Army General Hospital.Individualized surgical program were developed according to preoperative imaging examination and hepatic functional reserve examination. The evaluation included liver function, liver volume, vascular anatomy and bile duct anatomy. According to the results after the operation, preoperative evaluation accuracy, postoperative donor liver function and postoperative complications were analyzed. ANOVA analysis was used to compare the difference of graft volume by two-dimensional, three-dimensional calculation method and actual postoperative graft weight. Pearson correlation test and linear regression analysis were used to verify the correlation between the estimated graft volume each method and actual graft postoperative weight. RESULTS: All the 89 cases operation protocol as following, there were 5 cases with left lateral lobe graft, 10 cases with left lobe liver graft, 74 cases with right lobe graft. There were 59 cases with middle hepatic vein (MHV) harvested, and 30 cases without MHV. The mean graft volume by two-dimensional, three-dimensional calculation method and actual postoperative graft weight were (656.2±134.1) ml, (631.7±143.2) ml and (614.5±137.7) ml respectively. ANOVA analysis results showed that there were no statistically significant difference in the three methods (P>0.05). Compared to the actual postoperative graft weight, the average error rate of the two methods were 7.9% and 5.3% respectively. Pearson correlation test showed the graft volume calculated by two-dimensional and three-dimensional methods had a significantly positive correlation with actual graft weight (r=0.821, 0.890, P<0.01) and linear regression analyze showed the R2 were 0.674 and 0.792, respectively. The accuracy rate of preoperative evaluation about portal vein, hepatic vein, hepatic artery and bile duct were 100%, 100%, 97.8% and 95.5%, respectively. The preoperative plan and postoperative practical scheme coincidence rate was 95.5%. Overall donor complication rate was 7.4%. All donors were alive. Sixteen donors received right lobe hepatectomy with gallbladder preserved had a good liver function and gallbladder function. CONCLUSION: Through the precise preoperative evaluation, surgical planning, fine operation and excellent postoperative management, precise liver surgery technique can ensure the safety of donor in living donor liver transplantation.

Identifying and prioritizing disease-related genes based on the network topological features.

Identifying and prioritizing disease-related genes are the most important steps for understanding the pathogenesis and discovering the therapeutic targets. The experimental examination of these genes is very expensive and laborious, and usually has a higher false positive rate. Therefore, it is highly desirable to develop computational methods for the identification and prioritization of disease-related genes. In this study, we develop a powerful method to identify and prioritize candidate disease genes. The novel network topological features with local and global information are proposed and adopted to characterize genes. The performance of these novel features is verified based on the 10-fold cross-validation test and leave-one-out cross-validation test. The proposed features are compared with the published features, and fused strategy is investigated by combining the current features with the published features. And, these combination features are also utilized to identify and prioritize Parkinson's disease-related genes. The results indicate that identified genes are highly related to some molecular process and biological function, which provides new clues for researching pathogenesis of Parkinson's disease. The source code of Matlab is freely available on request from the authors.

Identifying functions of protein complexes based on topology similarity with random forest.

Elucidating the functions of protein complexes is critical for understanding disease mechanisms, diagnosis and therapy. In this study, based on the concept that protein complexes with similar topology may have similar functions, we firstly model protein complexes as weighted graphs with nodes representing the proteins and edges indicating interaction between proteins. Secondly, we use topology features derived from the graphs to characterize protein complexes based on the graph theory. Finally, we construct a predictor by using random forest and topology features to identify the functions of protein complexes. Effectiveness of the current method is evaluated by identifying the functions of mammalian protein complexes. And then the predictor is also utilized to identify the functions of protein complexes retrieved from human protein-protein interaction networks. We identify some protein complexes with significant roles in the occurrence of tumors, vesicles and retinoblastoma. It is anticipated that the current research has an important impact on pathogenesis and the pharmaceutical industry. The source code of Matlab and the dataset are freely available on request from the authors.

[Liver transplantation for irresectable hilar cholangiocarcinoma].

OBJECTIVE: To evaluate the outcome of patients with irresectable hilar cholangiocarcinoma undergoing orthotopic liver transplantation (OLT) and to identify the prognostic factors that could influence survival. METHODS: The data of 18 patients who underwent OLT for irresectable hilar cholangiocarcinoma between June 2003 and October 2010 were analyzed retrospectively. There were 12 male and 6 female cases with median of 52 years(range from 34 to 65 years).Fifteen patients underwent modified piggyback liver transplantation, 2 patients underwent classical orthotopic liver transplantation and 1 patient underwent living donor liver transplantation. Data were evaluated regarding tumor size, pathologic stage, overall survival, recurrence rates and prognostic factors. RESULTS: OLT with lymphadenectomy was received by 18 patients with hilar cholangiocarcinoma. Median time until tumor recurrence was 20.5 months(range from 6.0 to 33.0 months). Seventeen patients died during follow-up.Of these, 14 patients died from recurrent or metastatic diseases, 2 patients died from multiple organ dysfunction syndrome during peri-operative period, and one patient died from other cause. The median survival time was 29.5 months(range from 3.0 to 84.0 months). The overall survival rate and recurrence-free survival rate at 1, 3, and 5 year were 16/18, 8/18, 1/18 and 13/18, 2/18, 1/18, respectively.Lymph node metastases had a statistically significant negative impact on overall survival. The 1, 3, and 5 year survival rates were 6/7, 1/7,0 and 10/11, 7/11, 1/11 (P < 0.05) in lymph node-positive and lymph node-negative patients. CONCLUSIONS: Acceptable survival rates can be achieved by OLT for irresectable hilar cholangiocarcinoma without lymph node metastases.Strict patient selection plus multimodal chemoradiation therapy prior to OLT are recommend for patients with lymph node metastases.

Identifying subcellular localizations of mammalian protein complexes based on graph theory with a random forest algorithm.

In the post-genome era, one of the most important and challenging tasks is to identify the subcellular localizations of protein complexes, and further elucidate their functions in human health with applications to understand disease mechanisms, diagnosis and therapy. Although various experimental approaches have been developed and employed to identify the subcellular localizations of protein complexes, the laboratory technologies fall far behind the rapid accumulation of protein complexes. Therefore, it is highly desirable to develop a computational method to rapidly and reliably identify the subcellular localizations of protein complexes. In this study, a novel method is proposed for predicting subcellular localizations of mammalian protein complexes based on graph theory with a random forest algorithm. Protein complexes are modeled as weighted graphs containing nodes and edges, where nodes represent proteins, edges represent protein-protein interactions and weights are descriptors of protein primary structures. Some topological structure features are proposed and adopted to characterize protein complexes based on graph theory. Random forest is employed to construct a model and predict subcellular localizations of protein complexes. Accuracies on a training set by a 10-fold cross-validation test for predicting plasma membrane/membrane attached, cytoplasm and nucleus are 84.78%, 71.30%, and 82.00%, respectively. And accuracies for the independent test set are 81.31%, 69.95% and 81.00%, respectively. These high prediction accuracies exhibit the state-of-the-art performance of the current method. It is anticipated that the proposed method may become a useful high-throughput tool and plays a complementary role to the existing experimental techniques in identifying subcellular localizations of mammalian protein complexes. The source code of Matlab and the dataset can be obtained freely on request from the authors.

Fluorescence spectral analysis for the discrimination of complex, similar mixtures with the aid of chemometrics.

An analytical method for the classification of complex real-world samples was researched and developed with the use of excitation-emission fluorescence matrix (EEFM) spectroscopy, using the medicinal herbs, Rhizoma corydalis decumbentis (RCD) and Rhizoma corydalis (RC) as example samples. The data set was obtained from various authentic RCD-A and RC-A, adulterated AD, and commercial RCD-C and RC-C samples. The spectra (range: λ(ex) = 215∼395 nm and λ(em) = 290∼560 nm), arranged in two- and three-way data matrix formats, were processed using principal component analysis (PCA) and parallel factor analysis (PARAFAC) to produce two-dimensional component-by-component plots for qualitative data classification. The RCD-A and RC-A object groups were clearly discriminated, but the AD and the RCD-C as well as RC-C samples were less well separated. PARAFAC analysis produced somewhat better discrimination, and loadings plots revealed the presence of the marker compound Protopine-a strongly fluorescing substance-as well as at least two other unidentified fluorescent components. Classification performance of the common K-nearest neighbors (KNN) and linear discrimination analysis (LDA) methods was relatively poor when compared with that of the back propagation- and radial basis function-artificial neural networks (BP-ANN and RBF-ANN) models on the basis of two- and three-way formatted data. The best results were obtained with the three-way fingerprints and the RBF-ANN model. Subsequently, the quality of the commercial samples (RCD-C and RC-C) was classified on the best optimized RBF-ANN model. Thus, EEFM spectroscopy, which provides three-way measured data, is potentially a powerful analytical technique for the analysis of complex real-world substances provided the classification is performed by the RBF-ANN or similar ANN methods.

Identification of potential host proteins for influenza A virus based on topological and biological characteristics by proteome-wide network approach.

A proteome-wide network approach was performed to characterize significant patterns of influenza A virus (IAV)-human interactions, and to further identify potentially valuable targets for prophylactic and therapeutic interventions. Topological analysis demonstrated a strong tendency for IAV to interplay with highly connected and central proteins located in sparsely connected sub-networks. Additionally, functional analysis based on biological process revealed a number of functional groups overrepresented for IAV interactions, in which regulation of cell death and apoptosis, and phosphorus metabolic process is the most highly enriched. In order to investigate whether these topological and biological features are significant enough to distinguish IAV targets from human proteome, a discrimination model was constructed based on these features using support vector machine coupled with genetic algorithm. The average result of overall prediction accuracy is 71.04% by leave-one-out across validation test. The optimized classifier was then applied to 9706 human proteins. As a result, 1418 novel genes were identified from human interactome, some of which were experimentally validated by others' works to be important for IAV infection. The findings presented in this study might be important in discovering new drug targets for therapeutic treatments as well as revealing topological features and functional properties specific for viral infection.