Mass spectrometry investigation of glycosylation on the NXS/T sites in recombinant glycoproteins

We used a targeted proteomics approach to investigate whether introduction of new N-linked glycosylation sites in a chimeric protein influence the glycosylation of the existing glycosylation sites. To accomplish our goals, we over-expressed and purified a chimeric construct that contained the Fc region of the IgG fused to the exons 7 & 8 of mouse ZP3 (IgG-Fc-ZP3E7 protein). Immunoglobulin heavy chain (IgG-HC protein) was used as control. We then analyzed the IgG-HC and IgG-Fc-ZP3E7 proteins by liquid chromatography-tandem mass spectrometry (LC–MS/MS) and by Western blotting (WB). We concluded that in control experiments, the glycosylation site was occupied as expected. However, in the IgG-Fc-ZP3E7 protein, we concluded that only one out of three NXS/T glycosylation sites is occupied by N-linked oligosaccharides. We also concluded that in the IgG-Fc-ZP3E7 protein, upon introduction of additional potential NXS/T glycosylation sites within its sequence, the original NST/S glycosylation site from the Fc region of the IgG-Fc-ZP3E7 protein is no longer glycosylated. The biomedical significance of our findings is discussed.     

Helminth infections: Enabling the World Health Organization Road Map

Helminthiases are considered among the most persistent public health problems. Control and/or elimination remains a global health challenge and the World Health Organization Road Map highlights critical gaps and actions required to reach the 2030 targets, among them the need for new and more effective treatment options. Stronger collaborations across different fields are required to reach these goals. The helminth elimination platform is one example of how knowledge of two different disease areas can be aligned to fuse expertise and break disease silos.     

Prediction of prognosis of patients with lung cancer in combination with the immune score

Purpose: The host’s immune response to malignant tumor is fundamental to tumorigenesis and tumor development. The immune score is currently used to assess prognosis and to guide immunotherapy; however, its association with lung cancer prognosis is not clear.Methods: Clinical features and immune score data of lung cancer patients from The Cancer Genome Atlas were obtained to build a clinical prognosis nomogram. The model’s accuracy was verified by calibration curves.Results: In total, 1005 patients with lung cancer were included. Patients were divided into three groups according to low, medium, and high immune scores. Compared with patients in the low immune score group, the disease-free survival (DFS) of patients in medium and high immune score groups was significantly longer; the hazard ratio (HR) and 95% confidence interval (95% CI) were 0.77 [0.60–0.99] and 0.74 [0.60–0.91], respectively. The overall survival (OS) of patients in the medium and high immune score groups was significantly longer than in the low immune score group; the HR and 95% CI were 0.74 [0.57–0.96] and 0.69 [0.55–0.88], respectively. A clinical prediction model was established to predict the survival prognosis. As verified by calibration curves, the model showed good predictive ability, especially for predicting 3-/5-year DFS and OS.Conclusion: Patients with lung cancer with medium and high immune scores had longer DFS and OS than those in low immune score group. Patient prognosis can be effectively predicted by the clinical prediction model combining clinical features and immune score and was consistent with actual clinical outcomes.     

Testing inflated zeros in binomial regression models

Binomial regression models are commonly applied to proportion data such as those relating to the mortality and infection rates of diseases. However, it is often the case that the responses may exhibit excessive zeros; in such cases a zero‐inflated binomial (ZIB) regression model can be applied instead. In practice, it is essential to test if there are excessive zeros in the outcome to help choose an appropriate model. The binomial models can yield biased inference if there are excessive zeros, while ZIB models may be unnecessarily complex and hard to interpret, and even face convergence issues, if there are no excessive zeros. In this paper, we develop a new test for testing zero inflation in binomial regression models by directly comparing the amount of observed zeros with what would be expected under the binomial regression model. A closed form of the test statistic, as well as the asymptotic properties of the test, is derived based on estimating equations. Our systematic simulation studies show that the new test performs very well in most cases, and outperforms the classical Wald, likelihood ratio, and score tests, especially in controlling type I errors. Two real data examples are also included for illustrative purpose.     

Assessing the climate change effects on the distribution pattern of the Azerbaijan Mountain Newt (Neurergus crocatus)

Climate change is a grave danger for humans and a looming threat to Earth's biodiversity in the twenty-first century. Assessing the vulnerability of species to climate change is critical for practical conservation efforts. Due to their limited dispersal ability, amphibians are one of the most vulnerable groups of vertebrates to climate change. Among them, the species that inhabit mountains suffer a tremendous amount of climate change-induced pressures. We, therefore, adopted the Azerbaijan Mountain Newt (Neurergus crocatus), which currently inhabits Northwest Iran, North Iraq, and Southeast Turkey, as a case study for assessing the effects of climate change on the distribution patterns of mountain amphibians. By applying the species distribution models (SDMs) in this study, we tried to hindcast the species distribution area in the past and illustrate the impacts of climate change on its distribution in the present and future (the 2050s and 2070s) climate conditions. Also, the patch metrics have been deployed for identifying habitat fragmentation. Our results indicate a more than 50% rise in the species’ current suitable habitats compared to its glacial refugia. The suitable habitat is expected to gradually decrease in RCP 2.6 and RCP 8.5. Among the three countries in which the species occurs, its distribution overlaps with protected areas only in Iraq. The number of habitat patches will grow and reach approximately 20 to 60 patches by 2070 and the average area of the patches will decrease throughout this time. Aside from the numerous threats that endanger the species, climate change puts the long-term existence of Azerbaijan Newt in jeopardy. The results of this study stress the urgent need for taking extreme measures on the species management and conserving its remnant habitat patches.