Mathematical modelling for variations of inbreeding populations fitness with single and polygenic traits.

BACKGROUND: Inbreeding mating has been widely accepted as the key mechanism to enhance homozygosity which normally will decrease the fitness of the population. Although this result has been validated by a large amount of biological data from the natural populations, a mathematical proof of these experimental discoveries is still not complete. A related question is whether we can extend the well-established result regarding the mean fitness from a randomly mating population to inbreeding populations. A confirmative answer may provide insights into the frequent occurrence of self-fertilization populations. RESULTS: This work presents a theoretic proof of the result that, for a large inbreeding population with directional relative genotype fitness, the mean fitness of population increases monotonically. However, it cannot be extended to the case with over-dominant genotype fitness. In addition, by employing multiplicative intersection hypothesis, we prove that inbreeding mating does decrease the mean fitness of polygenic population in general, but does not decrease the mean fitness with mixed dominant-recessive genotypes. We also prove a novel result that inbreeding depression depends on not only the mating pattern but also genetic structure of population. CONCLUSIONS: For natural inbreeding populations without serious inbreeding depression, our theoretical analysis suggests the majority of its genotypes should be additive or dominant-recessive genotypes. This result gives a reason to explain why many hermaphroditism populations do not show severe inbreeding depression. In addition, the calculated purging rate shows that inbreeding mating purges the deleterious mutants more efficiently than randomly mating does.

Nitric oxide negatively regulates gibberellin signaling to coordinate growth and salt tolerance in Arabidopsis.

In response to dynamically altered environments, plants must finely coordinate the balance between growth and stress responses for their survival. However, the underpinning regulatory mechanisms remain largely elusive. The phytohormone gibberellin promotes growth via a derepression mechanism by proteasomal degradation of the DELLA transcription repressors. Conversely, the stress-induced burst of nitric oxide (NO) enhances stress tolerance, largely relying on NO-mediated S-nitrosylation, a redox-based posttranslational modification. Here, we show that S-nitrosylation of Cys-374 in the Arabidopsis RGA protein, a key member of DELLAs, inhibits its interaction with the F-box protein SLY1, thereby preventing its proteasomal degradation under salinity condition. The accumulation of RGA consequently retards growth but enhances salt tolerance. We propose that NO negatively regulates gibberellin signaling via S-nitrosylation of RGA to coordinate the balance of growth and stress responses when challenged by adverse environments.

Effects of Nano-Aerators on Microbial Communities and Functions in the Water, Sediment, and Shrimp Intestine in Litopenaeus vannamei Aquaculture Ponds.

Nanobubble technology has promising development and application prospects in the fields of sewage treatment, soil and groundwater remediation, animal and plant growth, and biomedicine. However, few studies have investigated its effect on shrimp aquaculture. In this study, we investigated the effect of nano-aerators on microbial communities of the water, sediment, and shrimp gut in a Litopenaeus vannamei aquaculture pond using 16S rRNA high-throughput sequencing. The results indicated that the nano-aerator significantly increased the microbial community diversity and species abundance in the pond, and the microbial community diversity of the pond sediment increased under short-term aeration conditions. Compared to that with ordinary aerators, nano-aerators increased the proportion of beneficial bacteria, such as Exiguobacterium and Acinetobacter, in the water and sediment microbial communities. Moreover, the proportions of beneficial bacteria in the gut, including Rhodobacter, Oscillospira, and Faecalibacterium, were all increased by using the nano-aerator. Therefore, our findings suggest that nano-aerators could promote the activity of beneficial bacteria in aquaculture ecosystems, thereby regulating water quality, reducing disease incidence, and improving aquaculture efficiency and benefits. Our findings provide new insights into the effects of nano-aerators on microbes in crustacean culture ponds.

Structure-Based Design of Highly Potent Toll-like Receptor 7/8 Dual Agonists for Cancer Immunotherapy.

Activation of the toll-like receptors 7 and 8 has emerged as a promising strategy for cancer immunotherapy. Herein, we report the design and synthesis of a series of pyrido[3,2-d]pyrimidine-based toll-like receptor 7/8 dual agonists that exhibited potent and near-equivalent agonistic activities toward TLR7 and TLR8. In vitro, compounds 24e and 25a significantly induced the secretion of IFN-α, IFN-γ, TNF-α, IL-1ß, IL-12p40, and IP-10 in human peripheral blood mononuclear cell assays. In vivo, compounds 24e, 24m, and 25a significantly suppressed tumor growth in CT26 tumor-bearing mice by remodeling the tumor microenvironment. Additionally, compounds 24e, 24m, and 25a markedly improved the antitumor activity of PD-1/PD-L1 blockade. In particular, compound 24e combined with the anti-PD-L1 antibody led to complete tumor regression. These results demonstrated that TLR7/8 agonists (24e, 24m, and 25a) held great potential as single agents or in combination with PD-1/PD-L1 blockade for cancer immunotherapy.

Hematopoietic Progenitor Kinase1 (HPK1) Mediates T Cell Dysfunction and Is a Druggable Target for T Cell-Based Immunotherapies.

Ameliorating T cell exhaustion and enhancing effector function are promising strategies for the improvement of immunotherapies. Here, we show that the HPK1-NFκB-Blimp1 axis mediates T cell dysfunction. High expression of MAP4K1 (which encodes HPK1) correlates with increased T cell exhaustion and with worse patient survival in several cancer types. In MAP4K1KO mice, tumors grow slower than in wild-type mice and infiltrating T cells are less exhausted and more active and proliferative. We further show that genetic depletion, pharmacological inhibition, or proteolysis targeting chimera (PROTAC)-mediated degradation of HPK1 improves the efficacy of CAR-T cell-based immunotherapies in diverse preclinical mouse models of hematological and solid tumors. These strategies are more effective than genetically depleting PD-1 in CAR-T cells. Thus, we demonstrate that HPK1 is a mediator of T cell dysfunction and an attractive druggable target to improve immune therapy responses.

Nickel-Catalyzed Decarboxylative Alkenylation of Anhydrides with Vinyl Triflates or Halides.

Decarboxylative cross-coupling of aliphatic acid anhydrides with vinyl triflates or halides was accomplished via nickel catalysis. This methodology works well with a broad array of substrates and features abundant functional group tolerance. Notably, our approach addresses the issue of safe and environmental installation of methyl or ethyl group into molecular scaffolds. The method possesses high chemoselectivity toward alkyl groups when aliphatic/aromatic mixed anhydrides are involved. Furthermore, diverse ketones could be modified with our strategy.

Instantaneous mutation rate in cancer initiation and progression.

BACKGROUND: Cancer is one of the leading causes for the morbidity and mortality worldwide. Although substantial studies have been conducted theoretically and experimentally in recent years, it is still a challenge to explore the mechanisms of cancer initiation and progression. The investigation for these problems is very important for the diagnosis of cancer diseases and development of treatment schemes. RESULTS: To accurately describe the process of cancer initiation, we propose a new concept of gene initial mutation rate based on our recently designed mathematical model using the non-constant mutation rate. Unlike the widely-used average gene mutation rate that depends on the number of mutations, the gene initial mutation rate can be used to describe the initiation process of a single patient. In addition, we propose the instantaneous tumour doubling time that is a continuous function of time based on the non-constant mutation rate. Our proposed concepts are supported by the clinic data of seven patients with advanced pancreatic cancer. The regression results suggest that, compared with the average mutation rate, the estimated initial mutation rate has a larger value of correlation coefficient with the patient survival time. We also provide the estimated tumour size of these seven patients over time. CONCLUSIONS: The proposed concepts can be used to describe the cancer initiation and progression for different patients more accurately. Since a quantitative understanding of cancer progression is important for clinical treatment, our proposed model and calculated results may provide insights into the development of treatment schemes and also have other clinic implications.

A new model of time scheme for progression of colorectal cancer.

BACKGROUND: tumourigenesis can be regarded as an evolutionary process, in which the transformation of a normal cell into a tumour cell involves a number of limiting genetic and epigenetic events. To study the progression process, time schemes have been proposed for studying the process of colorectal cancer based on extensive clinical investigations. Moreover, a number of mathematical models have been designed to describe this evolutionary process. These models assumed that the mutation rate of genes is constant during different stages. However, it has been pointed that the subsequent driver mutations appear faster than the previous ones and the cumulative time to have more driver mutations grows with the growing number of gene mutations. Thus it is still a challenge to calculate the time when the first mutation occurs and to determine the influence of tumour size on the mutation rate. RESULTS: In this work we present a general framework to remedy the shortcoming of existing models. Rather than considering the information of gene mutations based on a population of patients, we for the first time determine the values of the selective advantage of cancer cells and initial mutation rate for individual patients. The averaged values of doubling time and selective advantage coefficient determined by our model are consistent with the predictions made by the published models. Our calculation showed that the values of biological parameters, such as the selective advantage coefficient, initial mutation rate and cell doubling time diversely depend on individuals. Our model has successfully predicted the values of several important parameters in cancer progression, such as the selective advantage coefficient, initial mutation rate and cell doubling time. In addition, experimental data validated our predicted initial mutation rate and cell doubling time. CONCLUSIONS: The introduced new parameter makes our proposed model more flexible to fix various types of information based on different patients in cancer progression.