Bergaptol inhibits glioma cell proliferation and induces apoptosis via STAT3/Bcl-2 pathway.

Glioblastoma (GBM) is the most common primary malignant brain tumour and lacks therapeutic options with significant effects. The aberrant activation of STAT3 is a critical factor in glioma progression via activating multiple signalling pathways that promote glioma. Among them, the antiapoptotic gene Bcl-2 could be upregulated by p-STAT3, which is an important reason for the continuous proliferation of glioma. We previously reported that bergaptol, a natural furanocoumarin widely found in citrus products, exerts antineuroinflammatory effects by inhibiting the overactivation of STAT3. Here, we aimed to evaluate whether bergaptol could promote glioma apoptosis by inhibiting the STAT3/Bcl-2 pathway. This study found that bergaptol inhibited the proliferation and migration of GBM cell lines (U87 and A172) and promoted apoptosis in vitro. We also found that bergaptol significantly inhibited the STAT3/Bcl-2 pathway in GBM cells. U87 cells were implanted intracranially into nude mice to establish a glioma model, and glioma-bearing mice were treated with bergaptol (40 mg/kg). Bergaptol treatment significantly inhibited glioma growth and prolonged the glioma-bearing mice's survival time. In addition, bergaptol administration also significantly inhibited the STAT3/Bcl-2 pathway of tumour tissue in vivo. Overall, we found that bergaptol could effectively play an antiglioma role by inhibiting STAT3/Bcl-2 pathway, suggesting the potential efficacy of bergaptol in treating glioma.

Prediction of injury localization in preoperative patients with gastrointestinal perforation: a multiomics model analysis.

BACKGROUND: The location of gastrointestinal perforation is essential for severity evaluation and optimizing the treatment approach. We aimed to retrospectively analyze the clinical characteristics, laboratory parameters, and imaging features of patients with gastrointestinal perforation and construct a predictive model to distinguish the location of upper and lower gastrointestinal perforation. METHODS: A total of 367 patients with gastrointestinal perforation admitted to the department of emergency surgery in Fujian Medical University Union Hospital between March 2014 and December 2020 were collected. Patients were randomly divided into training set and test set in a ratio of 7:3 to establish and verify the prediction model by logistic regression. The receiver operating characteristic curve, calibration map, and clinical decision curve were used to evaluate the discrimination, calibration, and clinical applicability of the prediction model, respectively. The multiomics model was validated by stratification analysis in the prediction of severity and prognosis of patients with gastrointestinal perforation. RESULTS: The following variables were identified as independent predictors in lower gastrointestinal perforation: monocyte absolute value, mean platelet volume, albumin, fibrinogen, pain duration, rebound tenderness, free air in peritoneal cavity by univariate logistic regression analysis and stepwise regression analysis. The area under the receiver operating characteristic curve of the prediction model was 0.886 (95% confidence interval, 0.840-0.933). The calibration curve shows that the prediction accuracy and the calibration ability of the prediction model are effective. Meanwhile, the decision curve results show that the net benefits of the training and test sets are greater than those of the two extreme models as the threshold probability is 20-100%. The multiomics model score can be calculated via nomogram. The higher the stratification of risk score array, the higher the number of transferred patients who were admitted to the intensive care unit (P < 0.001). CONCLUSION: The developed multiomics model including monocyte absolute value, mean platelet volume, albumin, fibrinogen, pain duration, rebound tenderness, and free air in the peritoneal cavity has good discrimination and calibration. This model can assist surgeons in distinguishing between upper and lower gastrointestinal perforation and to assess the severity of the condition.

Structural identification of single boron-doped graphdiynes by computational XPS and NEXAFS spectroscopy.

Boron-doped graphdiyne (B-GDY) material exhibits an excellent performance in electrocatalysis, ion transport, and energy storage. However, accurately identifying the structures of B-GDY in experiments remains a challenge, hindering further selection of suitable structures with the most ideal performance for various practical applications. In the present work, we employed density functional theory (DFT) to simulate the X-ray photoelectron spectra (XPS) and near-edge X-ray absorption fine-structure (NEXAFS) spectra of pristine graphdiyne (GDY) and six representative single boron-doped graphdiynes at the B and C K-edges to establish the structure-spectroscopy relationship. A notable disparity in the C 1s ionization potentials (IPs) between substituted and adsorbed structures is observed upon doping with a boron atom. By analyzing the C and B 1s NEXAFS spectra on energy positions, spectral widths, spectral intensities, and different spectral profiles, we found that the six single boron-doped graphdiyne configurations can be sensitively identified. Moreover, this study provides a reliable theoretical reference for distinguishing different single boron-doped graphdiyne structures, enabling accurate selection of B-GDY structures for diverse practical applications.

Synthesis and Broadband Photodetection of a P-Type 1D Van der Waals Semiconductor HfSnS3.

1D van der Waals (vdW) materials have attracted significant interest in recent years due to their giant anisotropic and weak interlayer-coupled characters. More 1D vdW materials are urgently to be exploited for satisfying the practice requirement. Herein, the study of 1D vdW ternary HfSnS3 high-quality single crystals grown via the chemical vapor transport technique is reported. The Raman vibration modes and band structure of HfSnS3 are analyzed via DFT calculations. Its strong in-plane anisotropic is verified by the polarized Raman spectroscopy. The field-effect transistors (FETs) based on the HfSnS3 nanowires demonstrate p-type semiconducting behavior as well as outstanding photoresponse in a broadband range from UV to near-infrared (NIR) with short response times of ≈0.355 ms, high responsivity of ≈11.5 A W-1 , detectivity of ≈8.2 × 1011 , external quantum efficiency of 2739%, excellent environmental stability, and repeatability. Furthermore, a typical photoconductivity effect of the photodetector is illustrated. These comprehensive characteristics can promote the application of the p-type 1D vdW material HfSnS3 in optoelectronics.

Interpreting the Cu-O2 Antibonding Nature in Two Cu-O2 Complexes from Cu L-Edge X-ray Absorption Spectra.

Cu-O2 structures play important roles in bioinorganic chemistry and enzyme catalysis, where the bonding between the Cu and O2 parts serves as a fundamental research concern. Here, we performed a multiconfigurational study on the copper L2,3-edge X-ray absorption spectra (XAS) of two copper enzyme model complexes to gain a better understanding of the antibonding nature from the clearly interpreted structure-spectroscopy relation. We obtained spectra in good agreement with the experiments by using the restricted active space second-order perturbation theory (RASPT2) method, which facilitated reliable chemical analysis. Spectral feature interpretations were supported by computing the spin-orbit natural transition orbitals. All major features were assigned to be mainly from Cu 2p to antibonding orbitals between Cu 3d and O2 π*, Cu 3d-πO-O* (type A), and a few also to mixed antibonding/bonding orbitals between Cu 3d and O2 π, Cu 3d ± πO-O (type M). Our calculations provided a clear illustration of the interactions between Cu 3d and O2 π*/π orbitals that are carried in the metal L-edge XAS.

First-principles simulation of X-ray spectra of graphdiyne and graphdiyne oxides at the carbon K-edge.

The experimental C 1s near-edge X-ray absorption fine-structure (NEXAFS) spectra of graphdiyne (GDY) show an evident change at different exposure periods, which is explained by oxidation. Herein, to better understand the structure-spectra relationship and the influence of oxidization, we performed a first-principles simulation of the NEXAFS spectra and X-ray photoelectron spectra (XPS) of both pure GDY and its four typical graphdiyne oxides (GDO) at the carbon K-edge. Pure GDY contains one sp2-hybridized (C1) and two sp-hybridized (C2, C3) carbons, while oxidation introduces more nonequivalent carbons. The experimental NEXAFS spectrum exhibits the lowest peak at ca. 285.8 eV. It was found that the C 1s → π* excitation from the sp2-hybridized carbon atoms (C1) in pure GDY and the sp-hybridized atoms (C2, C3) in GDOs contributes to this peak. The two weak resonances at around 289.0 and 290.6 eV in the experiment are contributed by the carbon atoms bonded to the oxygen atoms. Meanwhile, we found that oxidization leads to an increase in the C 1s ionization potentials (IPs) by 0.3-2.7 eV, which is consistent with the XPS experiments. Our calculations provide a clear explanation of the structure-spectra relationships of GDY and GDOs, and the signatures are useful for estimating the degree of oxidation.

Prediction and management of strangulated bowel obstruction: a multi-dimensional model analysis.

BACKGROUND: Distinguishing strangulated bowel obstruction (StBO) from simple bowel obstruction (SiBO) still poses a challenge for emergency surgeons. We aimed to construct a predictive model that could distinctly discriminate StBO from SiBO based on the degree of bowel ischemia. METHODS: The patients diagnosed with intestinal obstruction were enrolled and divided into SiBO group and StBO group. Binary logistic regression was applied to identify independent risk factors, and then predictive models based on radiological and multi-dimensional models were constructed. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were calculated to assess the accuracy of the predicted models. Via stratification analysis, we validated the multi-dimensional model in the prediction of transmural necrosis both in the training set and validation set. RESULTS: Of the 281 patients with SBO, 45 (16.0%) were found to have StBO, while 236(84.0%) with SiBO. The AUC of the radiological model was 0.706 (95%CI, 0.617-0.795). In the multivariate analysis, seven risk factors including pain duration ≤ 3 days (OR = 3.775), rebound tenderness (OR = 5.201), low-to-absent bowel sounds (OR = 5.006), low levels of potassium (OR = 3.696) and sodium (OR = 3.753), high levels of BUN (OR = 4.349), high radiological score (OR = 11.264) were identified. The AUC of the multi-dimensional model was 0.857(95%CI, 0.793-0.920). In the stratification analysis, the proportion of patients with transmural necrosis was significantly greater in the high-risk group (24%) than in the medium-risk group (3%). No transmural necrosis was found in the low-risk group. The AUC of the validation set was 0.910 (95%CI, 0.843-0.976). None of patients in the low-risk and medium-risk score group suffered with StBO. However, all patients with bowel ischemia (12%) and necrosis (24%) were resorted into high-risk score group. CONCLUSION: The novel multi-dimensional model offers a useful tool for predicting StBO. Clinical management could be performed according to the multivariate score.

Who would avoid severe adverse events from nasointestinal tube in small bowel obstruction? A matched case-control study.

BACKGROUND: Nasointestinal tubes (NITs) have been increasingly used in patients with small bowel obstruction (SBO); However, severe adverse events (SAEs) of NITs might threaten the lives of patients. The indications of NITs need to be identified. This study was designed to explore the indications for the insertion of NITs in patients with SBO and to suggest the optimal strategies for individuals based on the outcomes of SAEs. METHODS: After propensity score matching, 68 pairs were included (Success group and failure group). The occurrence of SAEs and the clinical parameters were compared between the SAE group and the non-SAE group. Independent risk factors were evaluated among the subgroups. A novel scoring system was established to detect the subgroups that would benefit from NITs insertion. RESULTS: Successful implementation of NITs could avoid hypochloremia (p = 0.010), SAEs (p = 0.001), pneumonia (p = 0.006). SAEs occurred in 13 of 136 (9.6%) patients who accepted NITs insertion treatment. Risk factors for SAEs included tumors (p = 0.002), reduced BMI (p = 0.048), reduced hemoglobin (p = 0.001), abnormal activated partial thromboplastin time (p = 0.015) and elevated white blood cells (p = 0.002). A novel risk scoring system consists of hemoglobin before NITs insertion (95% CI 0.685, 0.893) and bowel obstruction symptoms relieved after NITs insertion (95% CI 0.575, 0.900) had the highest area under curve for predicting the occurrence of SAEs. We divided the risk score system into 3 grades, with the increasing grades, the rates of SAEs surged from 1.3% (1/74) to (6/11) 54.5%. CONCLUSION: NITs successfully insertion could avoid SAEs occurrence in SBO conservative treatment. SBO patients without anemia and could be relieved after NITs insertion could be the potential benefit group for this therapy.

A theoretical library of N1s core binding energies of polynitrogen molecules and ions in the gas phase.

Polynitrogen molecules and ions are important building blocks of high energy density compounds (HEDCs). High energy bonds formed at the N sites can be effectively probed by X-ray photoelectron spectroscopy (XPS) at the N K-edge. In this work, with the density functional theory and the ΔKohn-Sham scheme, we simulated the N1s ionic potentials (IPs) of 72 common polynitrogen molecules [tetrazoles, pentazole (N5H), diazines, triazines, tetrazines, furazans, oxazoles and oxadiazoles], ions [pentazolate anion (cyclo-N5-), pentazenium cation (N5+), etc.], and molecular (NH3⋯N5H, H2O⋯N5H) and ionic (NH4+⋯N5-, H3O+⋯N5-) pairs, as well as mononitrogen relatives. These constitute a small theoretical database for absolute N1s IPs with an average accuracy of ca. 0.3 eV. To understand the structure-IP relationship within this family, effects of side substituent and bridging groups, local bonding types (amine or imine N), charge and protonation states, and vibronic coupling were analyzed based on selected systems. This study in the gas phase collects inherent chemical shifts of nitrogen in high-energy NN and NC bonds, which provides an essential reference into XPS interpretations of more complex HEDCs in the solid state. We especially highlight the evident N1s chemical shifts induced by protonation for nitrogen in the five-membered ring (N5H versus cyclo-N5-, ca. 7 eV; NH3⋯N5H versus NH4+⋯N5-, ca. 3 eV; H2O⋯N5H versus H3O+⋯N5-, ca. 2 eV), and suggest XPS as a sensitive tool in determining the hydrogen positions in pentanitrogen-based HEDCs.

On the choice of shape and size for truncated cluster-based x-ray spectral simulations of 2D materials.

Truncated cluster models represent an effective way for simulating x-ray spectra of 2D materials. Here, we systematically assessed the influence of two key parameters, the cluster shape (honeycomb, rectangle, or parallelogram) and size, in x-ray photoelectron (XPS) and absorption (XAS) spectra simulations of three 2D materials at five K-edges (graphene, C 1s; C3N, C/N 1s; h-BN, B/N 1s) to pursue the accuracy limit of binding energy (BE) and spectral profile predictions. Several recent XPS experiments reported BEs with differences spanning 0.3, 1.5, 0.7, 0.3, and 0.3 eV, respectively. Our calculations favor the honeycomb model for stable accuracy and fast size convergence, and a honeycomb with ∼10 nm side length (120 atoms) is enough to predict accurate 1s BEs for all 2D sheets. Compared to all these experiments, predicted BEs show absolute deviations as follows: 0.4-0.7, 0.0-1.0, 0.4-1.1, 0.6-0.9, and 0.1-0.4 eV. A mean absolute deviation of 0.3 eV was achieved if we compare only to the closest experiment. We found that the sensitivity of computed BEs to different model shapes depends on systems: graphene, sensitive; C3N, weak; and h-BN, very weak. This can be attributed to their more or less delocalized π electrons in this series. For this reason, a larger cluster size is required for graphene than the other two to reproduce fine structures in XAS. The general profile of XAS shows weak dependence on model shape. Our calculations provide optimal parameters and accuracy estimations that are useful for x-ray spectral simulations of general graphene-like 2D materials.

CDKN2B antisense RNA 1 suppresses tumor growth in human colorectal cancer by targeting MAPK inactivator dual-specificity phosphatase 1.

Aberrant expression of long noncoding RNA cyclin-dependent kinase inhibitor 2B antisense RNA 1 (CDKN2B-AS1) has been detected in human colorectal cancer (CRC). This study aimed to investigate the role of CDKN2B-AS1 and the underlying mechanism in human CRC. Gain- and loss-of-function assays were performed to explore the role of CDKN2B-AS1 in the malignant behavior of HCT116 and SW480 CRC cells in vitro and in vivo. RNA pull-down assay was conducted to identify the target of CDKN2B-AS1 in CRC cells. The physical and functional interactions between CDKN2B-AS1 and the target were examined. CDKN2B-AS1 inhibited CRC cell proliferation and migration while promoting apoptosis in vitro via activation of mitogen-activated protein kinase kinases (MEK)/extracellular signal-regulated kinase (ERK)/p38 signaling. CDKN2B-AS1 bound to mitogen-activated protein kinase (MAPK) inactivator dual-specificity phosphatase 1 (DUSP1) in CRC cells. In contrast to CDKN2B-AS1, DUSP1 promoted CRC cell proliferation, suppressed apoptosis and inactivated MEK/ERK/p38 signaling in CRC cells. Furthermore, CDKN2B-AS1 overexpression attenuated DUSP1 expression in normal colonic myofibroblasts and CRC cells. Overexpression of DUSP1 effectively countered the activation of MEK/ERK/p38 signaling induced by CDKN2B-AS1 overexpression or further blocked MEK/ERK/p38 signaling suppressed by CDKN2B-AS1 silencing. In the mouse xenograft model, CDKN2B-AS1 suppressed CRC growth, whereas DUSP1 promoted CRC growth. CDKN2B-AS1 induced cell apoptosis while suppressing EMT (epithelial-mesenchymal transition), whereas DUSP1 suppressed cell apoptosis while inducing EMT in CRC, as evidenced by the alterations in the protein levels of apoptosis and EMT markers in tumor tissue samples. CDKN2B-AS1 regulates CRC cell growth and survival by targeting MAPK inactivator DUSP1.

A Novel Model for Landslide Displacement Prediction Based on EDR Selection and Multi-Swarm Intelligence Optimization Algorithm.

With the widespread application of machine learning methods, the continuous improvement of forecast accuracy has become an important task, which is especially crucial for landslide displacement predictions. This study aimed to propose a novel prediction model to improve accuracy in landslide prediction, based on the combination of multiple new algorithms. The proposed new method includes three parts: data preparation, multi-swarm intelligence (MSI) optimization, and displacement prediction. In the data preparation, the complete ensemble empirical mode decomposition (CEEMD) is adopted to separate the trend and periodic displacements from the observed cumulative landslide displacement. The frequency component and residual component of reconstructed inducing factors that related to landslide movements are also extracted by the CEEMD and t-test, and then picked out with edit distance on real sequence (EDR) as input variables for the support vector regression (SVR) model. MSI optimization algorithms are used to optimize the SVR model in the MSI optimization; thus, six predictions models can be obtained that can be used in the displacement prediction part. Finally, the trend and periodic displacements are predicted by six optimized SVR models, respectively. The trend displacement and periodic displacement with the highest prediction accuracy are added and regarded as the final prediction result. The case study of the Shiliushubao landslide shows that the prediction results match the observed data well with an improvement in the aspect of average relative error, which indicates that the proposed model can predict landslide displacements with high precision, even when the displacements are characterized by stepped curves that under the influence of multiple time-varying factors.

[Molecular cytogenetic study of a case with ring chromosome 15].

OBJECTIVE: To explore the genetic basis for a patient featuring developmental delay. METHODS: The patient and her parents were subjected to G- and C-banded chromosomal karyotyping analysis. The proband was also analyzed by single nucleotide polymorphism microarray (SNP-array). The result was verified by using fluorescence quantitative PCR (qPCR). RESULTS: The proband's karyotype was ascertained as 46,XX, r(15)(p11.2q26.3)[92]/45,XX,-15[9]/46,XX, dic r(15)(p11.2q26.3;p11.2q26.3)[4]. SNP-array revealed that she has carried a de novo deletion at 15q26.3 (98 957 555-102 429 040) spanning approximately 3.4 Mb, which encompassed the IGF1R gene. qPCR has confirmed haploinsufficiency of exons 3, 10 and 20 of the IGF1R gene. Both of her parents had a normal karyotype. CONCLUSION: The abnormal phenotype of the proband may be attributed to the microdeletion at 15q26.3, in particular haploinsuffiency of the IGF1R gene and instability of the ring chromosome. Cytogenetic method combined with SNP-array and qPCR can efficiently delineate chromosomal aberrations and provide accurate information for clinical diagnosis and genetic counseling.

Inferring fetal fractions from read heterozygosity empowers the noninvasive prenatal screening.

PURPOSE: Fetal fraction (FF) is the percent of cell-free DNA (cfDNA) in the mother's peripheral blood that is of fetal origin, which plays a pivotal role in noninvasive prenatal screening (NIPS). We present a method that can reliably estimate FFs by examining autosome single-nucleotide polymorphisms (SNPs). METHODS: Even at a very low sequencing depth, there are plenty of SNPs covered by more than one read. At those SNPs, we define read heterozygosity and demonstrate that the percent of read heterozygosity is a function of FF, which allows FF to be inferred. RESULTS: We first demonstrated the effectiveness of our method in inferring FF. Then we used the inferred FF as an informative alternative prior to computing Bayes factors to test for aneuploidy, and observed better power than the Z-test. In analysis of clinical samples, we were able to identify female-male twins thanks to the accurate FF inference. CONCLUSION: Knowing FF improves efficacy of NIPS. It brings a powerful Bayesian method, allows "no call" for samples with small FFs, renders screening for XXY syndrome simpler, and permits an adaptive design to sequence at a higher depth for samples with small FFs.

Correction: Inferring fetal fractions from read heterozygosity empowers the noninvasive prenatal screening.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A Hybrid Landslide Displacement Prediction Method Based on CEEMD and DTW-ACO-SVR-Cases Studied in the Three Gorges Reservoir Area.

Accurately predicting the surface displacement of the landslide is important and necessary. However, most of the existing research has ignored the frequency component of inducing factors and how it affects the landslide deformation. Therefore, a hybrid displacement prediction model based on time series theory and various intelligent algorithms was proposed in this paper to study the effect of frequency components. Firstly, the monitoring displacement of landslide from the Three Gorges Reservoir area (TGRA) was decomposed into the trend and periodic components by complete ensemble empirical mode decomposition (CEEMD). The trend component can be predicted by the least square method. Then, time series of inducing factors like rainfall and reservoir level was reconstructed into high frequency components and low frequency components with CEEMD and t-test, respectively. The dominant factors were selected by the method of dynamic time warping (DTW) from the frequency components and other common factors (e.g., current monthly rainfall). Finally, the ant colony optimization-based support vector machine regression (ACO-SVR) is utilized for prediction purposes in the TGRA. The results demonstrate that after considering the frequency components of landslide-induced factors, the accuracy of the displacement prediction model based on ACO-SVR is better than that of other models based on SVR and GA-SVR.

Design and Testing of Inertial System for Landslide Displacement Distribution Measurement.

Landslide displacement monitoring plays a fundamental role in the study of landslide evolution mechanisms, forecasting, risk assessment, prevention, and control. To fill the deficiencies of traditional instrumentation for measuring landslide displacement distributed along lateral direction, a landslide displacement measurement method based on deformation-coupled pipeline trajectory measurement is proposed, and a pipeline trajectory inertial measurement instrument is developed. The developed instrument, primarily comprised of a single shaft gyro, two axis accelerometers, and an external roller encoder, is designed as an axial half strapdown-radial half platform structure combined with a mechanical gravity platform. This structure avoids the singularity of pitch angle and roll angle and can expediently calculate a pipeline trajectory with an Eulerian transformation when obtaining several basic physical variables, e.g., the axial linear velocity, pitch angle, roll angle, and azimuth angle. Additionally, the pipeline trajectory, measured at different times, possesses the ability to reflect the displacement evolution feature of landslides. The results of prototype simulation tests imply a single measurement accuracy of a 12 cm/100 m span and a singly periodic multiple (more than five times) measurement accuracy of a 3 cm/100 m span, which meets medium-precision displacement measurement requirements for a landslide. Additionally, the finished instrument has been successfully applied to the deformation monitoring of the Majiagou I# landslide, which further verifies its feasibility and offers a reference for similar landslides.

[Genetic study of a child with developmental delay and mental retardation].

OBJECTIVE: To explore the genetic basis for a child with developmental delay and mental retardation. METHODS: Chromosomal karyotype of the child was analyzed by G-, C- and N-banding techniques. Her genome DNA was analyzed with single nucleotide polymorphisms array (SNP array). The result was validated by fluorescence quantitative polymerase chain reaction (PCR). RESULTS: The karyotype of the child was ascertained as 46,XX,r(22)(p12q13). SNP array has revealed a deletion of approximately 1.4 Mb at 22q13.33 (49 802 963-51 197 766). The deletion has encompassed the SHANK3, a crucial gene for the development of nervous system. Fluorescence quantitative PCR has confirmed the deletion of exons 7, 19 and 22 of the SHANK3 gene. CONCLUSION: The phenotype of the patient may be attributed to the microdeletion at 22q13.33. Cytogenetic methods combined with SNP array and fluorescence quantitative PCR can identify aberrant chromosomes and provide accurate information for the clinical diagnosis and genetic counseling.

DNA prime-protein boost vaccine encoding HLA-A2, HLA-A24 and HLA-DR1 restricted epitopes of CaNA2 against visceral leishmaniasis.

Visceral leishmaniasis is a tropical and neglected disease with an estimated 200 000-400 000 cases and 60 000 deaths worldwide each year. Currently, no clinically valid vaccine is available for this disease. In this study, we formulated DNA and protein vaccines encoding HLA-A2, HLA-A24 and HLA-DR1 restricted epitopes of CaNA2 against visceral leishmaniasis. We predicted the secondary and tertiary structures, surface properties, subcellular localization, potential binding sites and HLA-A2, HLA-A24 and HLA-DR1 restricted epitopes of CaNA2. The best candidate CpG ODN (2395, M362, D-SL03 or 685) was screened out as a DNA vaccine adjuvant. We also prepared Kmp-11 and Kmp-11/CaNA2 DNA and protein vaccines, respectively, for comparison. BALB/c mice were immunized with a DNA prime-protein boost immunization strategy and challenged with a newly isolated Leishmania strain from an individual with visceral leishmaniasis. The IgG antibody titers showed that our vaccine had strong immunogenicity with a long duration, especially cellular immunity. The spleen parasite burden of each group demonstrated that the CaNA2 vaccine had a certain immune protective effect on visceral leishmaniasis in BALB/c mice, and the amastigote reduction rate reached 76%. Preliminary safety tests confirmed the safety of the vaccine. Our work demonstrates that the HLA-A2, HLA-A24 and HLA-DR1 restricted epitope CaNA2 DNA prime-protein boost vaccine may be a safe and effective epitope vaccine candidate against visceral leishmaniasis.

Direct thiocarbamation of imidazoheterocycles via dual C-H sulfurization.

A copper-catalyzed DTBP oxidative dual C-H sulfurization has been developed for the direct thiocarbamation of imidazopyridines using a combination of elemental sulfur and formamides as carbamothioyl surrogates. NBS (bromo succinimide) was found to promote the thiocarbamation in good yields. This dual C-H sulfurization strategy enables access to a wide range of carbamothioyl imidazoheterocycles without the use of highly toxic phosgene.