Design, synthesis, biological evaluation of urea substituted 1,2,5-oxadiazole-3-carboximidamides as novel indoleamine 2,3-dioxygenase-1 (IDO1) inhibitors.

Indoleamine 2,3-dioxygenase-1 (IDO1) has been considered as an attractive target for oncology immunotherapy due to its immunosuppressive effects on the tumor microenvironment. The most advanced IDO1 inhibitor epacadostat in combination with anti-PD-1 antibody failed to show desirable objective response. Epacadostat is now reevaluated in phase III clinical trials, but its pharmacokinetic (PK) properties are unsatisfactory. To further unravel the antitumor efficacy of IDO1 inhibitors, we designed a series of epacadostat analogues by introducing various urea-containing side chains. In particular, the most active compound 3 showed superior inhibitory potency against recombinant hIDO1 and hIDO1 in HeLa cells induced by interferon γ (IFNγ) relative to epacadostat (3, biochemical hIDO1 IC50 = 67.4 nM, HeLa hIDO1 IC50 = 17.6 nM; epacadostat, biochemical hIDO1 IC50 = 75.9 nM, HeLa hIDO1 IC50 = 20.6 nM). Moreover, compound 3 exhibited improved physicochemical properties and rat PK profile with better oral exposure and bioavailability compared with epacadostat. Importantly, this compound exhibited comparable antitumor efficacy with epacadostat in LLC syngeneic xenograft models. Hence, compound 3 represents a promising lead compound for discovery of more effective IDO1 inhibitors.

Relationship between the Electrical Characteristics of Molecules and Fast Streamers in Ester Insulation Oil.

The effects of C=C, ester and ß-H groups on the ionization potential (IP) and electron affinity (EA) of molecules in natural ester insulation oil were investigated by density functional theory (DFT). The major contribution to the highest occupied molecular orbital (HOMO) comes from the carbon atoms adjacent to C=C. Thus, the IPs of triglycerides decrease as the number of C=C double bonds increases. The C=C in alkanes may also lower the IP. However, the ß-H in triglycerides has little effect on the IP, and C=C and ß-H have only a small effect on the EAs of the triglycerides because of the major contributions of atoms near the ester group in triglycerides to the lowest unoccupied molecular orbital (LUMO). This study calculated the IPs of 53 kinds of molecules in FR3, which are significantly lower compared with those of molecules in mineral oil (MO) and trimethylolpropane triester without C=C. However, the lightning impulse breakdown voltage (LI Vb) of trimethylolpropane triester is still significantly lower than that of MO at the large gap. Therefore, the transition from slow to fast streamers under low lighting impulse voltage is determined by the ester group rather than by C=C and ß-H. The ester group may attract more electrons, impacting itself more compared to alkane in MO and facilitating the transition from slow to fast streamers.

Protein Biomarkers in Serum of Patients with Schizophrenia.

This study was devised to identify potential biomarkers of schizophrenia (SP) using proteomics techniques. We obtained 44 serum specimens from patients with SP, 26 specimens from patients with depression, and 40 specimens from healthy controls. Immobilized metal affinity capture protein chips (IMAC30) and surface-enhanced laser desorption-ionization time-of-flight mass spectrometry were used to isolate and obtain mass spectrometric data of differentially expressed serum proteins. The sequences of the peaks discrepant among the study groups were obtained using matrix-assisted laser desorption/ionization mass spectrometry and proteins identified using Mascot database. In the SP group, there were 91 protein peaks that were different from other study groups at the p value of <0.05 and 54 peaks different at the p value of <0.01. Two protein peaks at the mass-to-charge ratio of 1,207.41 and 1,466.78 were markedly different among the study groups, with the lowest expression in specimens from patients with SP. The amino acid sequences were, respectively, Glu-Gly-Asp-Phe-Leu-Ala-Glu-Gly-Gly-Gly-Val-Arg (EGDFLAEGGGVR) and Asp-Ser-Gly-Glu-Gly-Asp-Phe-Leu-Ala-Glu-Gly-Gly-Gly-Val-Arg (DSGEGDFLAEGGGVR). These proteins were identified as the N-terminal fragments of fibrinogen. In conclusion, these biomarker proteins may be useful for molecular diagnosis of SP.

MicroRNAs in body fluids as biomarkers for non-small cell lung cancer: a systematic review.

Non-small cell lung cancer (NSCLC) is one of the most common life-threatening malignant tumors. A test for early diagnosis of NSCLC needs to be not too invasive and not too heavy a burden for weakened patients. A series of studies reported various microRNAs (miRNAs) could be novel serum biomarkers for NSCLC. However, the diagnostic ability of different miRNA biomarkers varies among the reports. The goal of this study was to perform a systematic review to examine the effect of miRNAs on NSCLC-related outcomes. We systematically searched The Cochrane Central Register of Controlled Trials, MEDLINE, Pub Med, EMBASE, the Chinese Biomedical Literature Database, the China Academic Journals Full-text Database, and the Chinese Scientific Journals Database for potential studies. Studies were included if they were related to miRNAs, NSCLC, and reported diagnostic outcomes. Diagnostic values analysis was used to summarize the overall test performance of miRNAs. 13 studies were included in this systematic review. The ranges of sensitivity (SEN) and specificity (SPE) of diagnosis model with miRNAs as identifying NSCLC were 0.69˜1.00 and 0.66˜1.00, respectively. The overall area under the curve (AUC) value of summary receiver operating characteristic (SROC) curve was 0.9151. The ranges of positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were 2.33˜24.75 and 0.010.40, respectively. The range of diagnostic odds ratio (DOR) was 6.52˜983.38. The current evidence indicates that miRNAs in body fluids show high accuracy in identifying NSCLC, and could be a useful screening tool for diagnosing NSCLC patients.

[Diagnosis model of idiopathic thrombocytopenic purpura based on platelet differential proteome].

This study was purposed to establish a new quick and simple diagnostic method with high sensitivity and good specificity for idiopathic thrombocytopenic purpura (ITP) and to evaluate its significance. 240 platelet lysates (from patients with ITP, leukemia, MDS, and healthy adults, each of 60 cases) were randomly assigned to training set (120 cases) or validation set (120 cases), all of them were detected by surface enhanced laser desorption ionization time of flight mass spectrometry (SELDI-TOF-MS), in order to identify the differentially expressed protein, the diagnostic model was established by means of artificial neural network (ANN), and was validated by blind test with SPSS 17.0. The results showed that 5 marked proteins significantly differentially expressed (P < 0.01), m/z of highly expressed proteins were 2234.30, 3476.36, and 7526.29, m/z of low expressed proteins were 4990.02 and 5152.39, respectively. The sensitivity and specificity of diagnostic model were 80.6% and 77.3% respectively. The area under the ROC curve consisting of the output value of artificial neura1 network was 0.837. Efficacy of the model was validated by means of blinded test. It is concluded that the ANN model is useful for clinical diagnosis of ITP on the basis of platelet protein fingerprint spectrum.

Application of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry coupled with an artificial neural network model for the diagnosis of hepatocellular carcinoma.

BACKGROUND/AIMS: There are no satisfactory biomarkers for hepatocellular carcinoma (HCC). The surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technique has been used to identify biomarkers for cancer. METHODOLOGY: Four hundred thirty five serum samples were tested by SELDI-TOF-MS matching on a gold chip. Samples were assigned to a training set and a testing set according to collection order. The training set was used to identify statistically significant peaks and to develop the artificial neural network (ANN) model for diagnosing HCC. The testing set was used in a blind test to validate the diagnostic efficiency of the ANN model. RESULTS: A total of 75 proteins that differed between patients and controls were identified (p<0.05). Seven of these proteins (p<0.01; m/z at 4207Da, 6604Da, 7734Da, 8106Da, 8545Da, 8599Da, 8894Da) were chosen to develop the ANN model. The model was subjected to a blind test using the testing set for HCC diagnosis. Sensitivity and specificity were 84.00% and 81.25%, respectively, and the accuracy was 81.90%. CONCLUSIONS: These results suggest that patients with HCC may have serum proteins that differ from healthy controls. The ANN is a new method for diagnosing and identifying HCC.