Tidal Effects on Circulation in and near the East China Sea

We incorporate tidal currents into a previously validated, three-dimensional, subtidal circulation model to assess tidal effects on the circulation in and around the East China Sea. Of particular interest is the tide-enhanced Changjiang plume dispersal and circulation in the southern East China Sea. The modeling results show that without tides, the Changjiang plume in summer presents itself as a stagnant, expansive pool in regions bordering the northern East China Sea and Yellow Sea, too far north and too accumulating relative to observations. The winter plume dispersal pushed by the north-northeast monsoon follows the China coastline southeastward as a coastal current that matches more closely with observations with or without tides. Incorporating the effect of tides brings the model closer to observation, especially in summer. During summer the Taiwan Warm Current shifts to lower latitudes, enhances upwelling off southeast China and induces a southward tidal residual coastal flow off southeast China. Tides also induce the observed seaward detachment of the summer plume. In winter, the prevailing north-northeast monsoon suppresses the Taiwan Warm Current to the minimum. However, if the winter monsoon is weakened for a few weeks, the Taiwan Warm Current reappears and these three mechanisms begin to operate as in summer. CTD surveys and satellite observations south of the Changjiang River estuary contribute to a better understanding of the tidal effects on regional ocean currents

Critical quality attributes (CQAs) of a therapeutic antibody produced from integrated continuous bioprocessing

The integrated continuous bioprocess provides an innovative way to produce protein drugs with flexibility and efficiency. However, during the long-term cultivation and complicated production, how to ensure the process stability and product quality is critically important. In this study, the monoclonal antibody (mAb) was produced in a bioreactor operated in a perfusion mode utilizing the ATF cell retention system for up to 32 days. The 2L harvest per day starting at day 10 was continuously purified using the 3-column periodic counter-current (PCC) chromatography system. The first protein A capture purification was performed with the dynamic binding capacity of 50% breakthrough around 60 mg mAb/mL of resin (vs 20 mg/mL resin for batch purification) for 120 cycles or 360 column operations followed by a polishing step of mixed mode chromatography for 20 cycles. The process and quality attributes were monitored daily. The results demonstrate consistency in both the purification process and the mAb qualities (in the aspects of product integrity, aggregates, and glycan profile) between PCC and batch purifications. Culture-related charge heterogeneity was observed accompanied by an increase of bioreactor harvest time using both batch and PCC purification processes. In addition, the impurities such as endotoxin and HCP were also monitored while under this high capacity utilization of chromatography resins. By sharing the insights of process and quality attributes, we hope to provide better understanding on the process-related heterogeneity between batch and continuous production and/or purification

A Deep Learning Approach for Predicting Antidepressant Response in Major Depression Using Clinical and Genetic Biomarkers

In the wake of recent advances in scientific research, personalized medicine using deep learning techniques represents a new paradigm. In this work, our goal was to establish deep learning models which distinguish responders from non-responders, and also to predict possible antidepressant treatment outcomes in major depressive disorder (MDD). To uncover relationships between the responsiveness of antidepressant treatment and biomarkers, we developed a deep learning prediction approach resulting from the analysis of genetic and clinical factors such as single nucleotide polymorphisms (SNPs), age, sex, baseline Hamilton Rating Scale for Depression score, depressive episodes, marital status, and suicide attempt status of MDD patients. The cohort consisted of 455 patients who were treated with selective serotonin reuptake inhibitors (treatment-response rate = 61.0%; remission rate = 33.0%). By using the SNP dataset that was original to a genome-wide association study, we selected 10 SNPs (including ABCA13 rs4917029, BNIP3 rs9419139, CACNA1E rs704329, EXOC4 rs6978272, GRIN2B rs7954376, LHFPL3 rs4352778, NELL1 rs2139423, NUAK1 rs2956406, PREX1 rs4810894, and SLIT3 rs139863958) which were associated with antidepressant treatment response. Furthermore, we pinpointed 10 SNPs (including ARNTL rs11022778, CAMK1D rs2724812, GABRB3 rs12904459, GRM8 rs35864549, NAALADL2 rs9878985, NCALD rs483986, PLA2G4A rs12046378, PROK2 rs73103153, RBFOX1 rs17134927, and ZNF536 rs77554113) in relation to remission. Then, we employed multilayer feedforward neural networks (MFNNs) containing 1–3 hidden layers and compared MFNN models with logistic regression models. Our analysis results revealed that the MFNN model with 2 hidden layers (area under the receiver operating characteristic curve (AUC) = 0.8228 ± 0.0571; sensitivity = 0.7546 ± 0.0619; specificity = 0.6922 ± 0.0765) performed maximally among predictive models to infer the complex relationship between antidepressant treatment response and biomarkers. In addition, the MFNN model with 3 hidden layers (AUC = 0.8060 ± 0.0722; sensitivity = 0.7732 ± 0.0583; specificity = 0.6623 ± 0.0853) achieved best among predictive models to predict remission. Our study indicates that the deep MFNN framework may provide a suitable method to establish a tool for distinguishing treatment responders from non-responders prior to antidepressant therapy

Genome-Wide Gene-Environment Interaction Analysis Using Set-Based Association Tests

The identification of gene-environment interactions (G × E) may eventually guide health-related choices and medical interventions for complex diseases. More powerful methods must be developed to identify G × E. The “adaptive combination of Bayes factors method” (ADABF) has been proposed as a powerful genome-wide polygenic approach to detect G × E. In this work, we evaluate its performance when serving as a gene-based G × E test. We compare ADABF with six tests including the “Set-Based gene-EnviRonment InterAction test” (SBERIA), “gene-environment set association test” (GESAT), etc. With extensive simulations, SBERIA and ADABF are found to be more powerful than other G × E tests. However, SBERIA suffers from a power loss when 50% SNP main effects are in the same direction with the SNP × E interaction effects while 50% are in the opposite direction. We further applied these seven G × E methods to the Taiwan Biobank data to explore gene× alcohol interactions on blood pressure levels. The ADAMTS7P1 gene at chromosome 15q25.2 was detected to interact with alcohol consumption on diastolic blood pressure (p = 9.5 × 10−7, according to the GESAT test). At this gene, the P-values provided by other six tests all reached the suggestive significance level (p < 5 × 10−5). Regarding the computation time required for a genome-wide G × E analysis, SBERIA is the fastest method, followed by ADABF. Considering the validity, power performance, robustness, and computation time, ADABF is recommended for genome-wide G × E analyses

EXAFS Peaks and TPR Characterizing Bimetallic Interactions: Effects of Impregnation Methods on the Structure of Pt-Ru/C Catalysts

To investigate bimetallic interactions, Pt-Ru/C catalysts were prepared by coimpregnation (Pt-Ruco/C) and successive impregnation (Ru-Ptse/C), while Pt/C, Ru/C, and reduced Pt-Rublack were used as reference. Those samples were characterized by XAS and TPR. When Pt(absorber)-Ru(backscatter) phase-and-amplitude correction is applied to Fourier transformed (FT) EXAFS of Pt-Rublack at Pt edge, the characteristic peak of Pt-Ru interactions appears at 2.70 Å´, whereas, when Pt-Pt correction is applied, the peak appears at about 2.5 Å´. Detailed EXAFS analysis for Pt-Ruco/C and Pt-Ruse/C confirms the nature of the characteristic peak and further indicates that the interactions can semiquantitatively be determined by the relative intensity between Pt-Ru and Pt-Pt characteristic peaks. This simple method in determining bimetallic interaction can be extended to characterize Pt-Pd/γ-Al2O3. However, for Pt-Re/γ-Al2O3, Pt-Re interactions cannot be determined by the method because of the overlap of Pt-Pt and Pt-Re characteristic peaks due to similar phase functions

Association between Parathyroid Hormone Levels and Inflammatory Markers among US Adults

Background and Aims. High levels of parathyroid hormone (PTH) appear to be associated with an increased mortality. Previous studies concerning the relationship of inflammatory markers with hyperparathyroidism have yielded inconsistent results. This study investigated whether serum PTH concentrations were independently associated with several inflammatory markers among the US adults. Materials and Methods. Using data from the National Health and Nutrition Examination Survey, we examined the relation between serum PTH and C-reactive protein (CRP), red cell distribution width (RDW), and platelet-to-lymphocyte ratio (PLR) levels with weighted linear regression. Additionally, we examined the relation with increased modified Glasgow Prognostic Score (mGPS) by using weighted logistic regression. Results. CRP, RDW, and PLR values increased with increasing serum PTH concentration. After extensively adjusting for covariates, CRP and RDW increased linearly and across PTH categories (all P<0.001), while PLR marginally increased (P=0.190 and P=0.095 using PTH as a categorical and continuous variable, resp.). The odds ratio of increased mGPS was 1.11 and 1.31 across PTH categories and with increasing PTH levels continuously. Conclusion. These nationally representative data indicate that serum PTH levels are independently associated with several inflammatory markers in the US population. The casual relationship between PTH levels and inflammation remains to be elucidated

Apoptosis induction in BEFV-infected Vero and MDBK cells through Src-dependent JNK activation regulates caspase-3 and mitochondria pathways

Our previous report demonstrated that bovine ephemeral fever virus (BEFV)-infected cultured cells could induce caspase-dependent apoptosis. This study aims to further elucidate how BEFV activates the caspase cascade in bovine cells. BEFV replicated and induced apoptosis in Vero and Madin-Darby bovine kidney (MDBK) cells, and a kinetic study showed a higher efficiency of replication and a greater apoptosis induction ability of BEFV in Vero cells. Src and c-Jun N-terminal kinase (JNK) inhibitor, but not extracellular signal-regulated kinase (ERK) or p38 inhibitor, alleviated BEFV-mediated cytopathic effect and apoptosis. In BEFV-infected Vero and MDBK cells, BEFV directly induced Src tyrosine-418 phosphorylation and JNK phosphorylation and kinase activity, which was inhibited specifically by SU6656 and SP600125, respectively. The caspase cascade and its downstream effectors, Poly (ADP-ribose) polymerase (PARP) and DFF45, were also activated simultaneously upon BEFV infection. In addition, cytochrome c, but not Smac/DIABLO, was released gradually from mitochondria after BEFV infection. SU6656 suppressed Src, JNK, and caspase-3 and -9 activation, as well as PARP and DFF45 cleavage; SP600125 reduced JNK and caspase-3 and -9 activation, as well as PARP and DFF45 cleavage. Taken together, these results strongly support the hypothesis that a Src-dependent JNK signaling pathway plays a key role in BEFV-induced apoptosis. The molecular mechanism identified in our study may provide useful information for the treatment of BEFV

Toll-like receptor 9 agonist enhances anti-tumor immunity and inhibits tumor-associated immunosuppressive cells numbers in a mouse cervical cancer model following recombinant lipoprotein therapy

BACKGROUND: Although cytotoxic T lymphocytes (CTLs) play a major role in eradicating cancer cells during immunotherapy, the cancer-associated immunosuppressive microenvironment often limits the success of such therapies. Therefore, the simultaneous induction of cancer-specific CTLs and reversal of the immunosuppressive tumor microenvironment may be more effectively achieved through a single therapeutic vaccine. A recombinant lipoprotein with intrinsic Toll-like receptor 2 (TLR2) agonist activity containing a mutant form of E7 (E7m) and a bacterial lipid moiety (rlipo-E7m) has been demonstrated to induce robust CTL responses against small tumors. This treatment in combination with other TLR agonists is able to eliminate large tumors. METHODS: Mouse bone marrow-derived dendritic cells (DCs) were employed to determine the synergistic production of pro-inflammatory cytokines upon combination of rlipo-E7m and other TLR agonists. Antigen-specific CTL responses were investigated using immunospots or in vivo cytolytic assays after immunization in mice. Mice bearing various tumor sizes were used to evaluate the anti-tumor effects of the formulation. Specific subpopulations of immunosuppressive cells in the tumor infiltrate were quantitatively determined by flow cytometry. RESULTS: We demonstrate that a TLR9 agonist (unmethylated CpG oligodeoxynucleotide, CpG ODN) enhances CTL responses and eradicates large tumors when combined with rlipo-E7m. Moreover, combined treatment with rlipo-E7m and CpG ODN effectively increases tumor infiltration by CTLs and reduces the numbers of myeloid-derived suppressor cells (MDSCs), tumor-associated macrophages (TAMs) and regulatory T cells (Tregs) in the tumor microenvironment. CONCLUSION: These findings suggest that the dramatic anti-tumor effects of the recombinant lipoprotein together with CpG ODN may reflect the amplification of CTL responses and the repression of the immunosuppressive environment. This promising approach could be applied for the development of additional therapeutic cancer vaccines