In order to inhibit pathogenic complications and to enhance animal and poultry growth, antibiotics have been extensively used for many years. Antibiotics applications not only affect target pathogens but also intestinal beneficially microbes, inducing long-lasting changes in intestinal microbiota associated with diseases. The application of antibiotics also has many other side effects like, intestinal barrier dysfunction, antibiotics residues in foodstuffs, nephropathy, allergy, bone marrow toxicity, mutagenicity, reproductive disorders, hepatotoxicity carcinogenicity, and antibiotic-resistant bacteria, which greatly compromise the efficacy of antibiotics. Thus, the development of new antibiotics is necessary, while the search for antibiotic alternatives continues. Probiotics are considered the ideal antibiotic substitute; in recent years, probiotic research concerning their application during pathogenic infections in humans, aquaculture, poultry, and livestock industry, with emphasis on modulating the immune system of the host, has been attracting considerable interest. Hence, the adverse effects of antibiotics and remedial effects of probiotics during infectious diseases have become central points of focus among researchers. Probiotics are live microorganisms, and when given in adequate quantities, confer good health effects to the host through different mechanisms. Among them, the regulation of host immune response during pathogenic infections is one of the most important mechanisms. A number of studies have investigated different aspects of probiotics. In this review, we mainly summarize recent discoveries and discuss two important aspects: (1) the application of probiotics during pathogenic infections; and (2) their modulatory effects on the immune response of the host during infectious and non-infectious diseases.

Since the discovery of cell apoptosis, other gene-regulated cell deaths are gradually appreciated, including pyroptosis, ferroptosis, and necroptosis. Necroptosis is, so far, one of the best-characterized regulated necrosis. In response to diverse stimuli (death receptor or toll-like receptor stimulation, pathogenic infection, or other factors), necroptosis is initiated and precisely regulated by the receptor-interacting protein kinase 3 (RIPK3) with the involvement of its partners (RIPK1, TRIF, DAI, or others), ultimately leading to the activation of its downstream substrate, mixed lineage kinase domain-like (MLKL). Necroptosis plays a significant role in the host’s defense against pathogenic infections. Although much has been recognized regarding modulatory mechanisms of necroptosis during pathogenic infection, the exact role of necroptosis at different stages of infectious diseases is still being unveiled, e.g., how and when pathogens utilize or evade necroptosis to facilitate their invasion and how hosts manipulate necroptosis to counteract these detrimental effects brought by pathogenic infections and further eliminate the encroaching pathogens. In this review, we summarize and discuss the recent progress in the role of necroptosis during a series of viral, bacterial, and parasitic infections with zoonotic potentials, aiming to provide references and directions for the prevention and control of infectious diseases of both human and animals.

The normal-to-tangential fracture compliance ratio is usually used as a fracture fluid indicator (FFI) for fluid identification in fractured reservoirs. With a new parameterization for fracture weaknesses, we have defined a new FFI based on azimuthally anisotropic elastic impedance (EI) inversion and fractured anisotropic rock-physics models. First, we derived a new azimuthally anisotropic EI equation with a similar expression for the isotropic and anisotropic EI parts to remove the exponential correction of EI that is attributable to weak anisotropy. Then, we built a fractured anisotropic rock-physics model used for the estimation of well-log parameters for the normal and tangential fracture weaknesses, which built the initial background low-frequency trend of fracture weaknesses. Finally, based on the azimuthally anisotropic EI inversion method with the Cauchy-sparse and low-frequency information regularization, we estimated an FFI applied to fluid identification in fractured reservoirs. Tests on the synthetic and real data demonstrate that the anisotropic parameters related to fracture weaknesses can be estimated reasonably and stably and that our method appears to provide an alternative available for fluid identification in fractured reservoirs.

Seismic data interpolation is an effective way to reconstruct missing seismic traces and to improve the quality of the seismic data set. In the field of deep learning, generative adversarial networks are capable of data generation and interpolation and have been widely used for high-quality image generations and image interpolations. In this letter, we propose a dual-domain conditional generative adversarial network (DD-CGAN) for seismic data interpolation. The DD-CGAN consists of a generator network and a discriminator network and uses the seismic data set and discrete Fourier transformed data set in the frequency domain as input vectors. The loss function of the DD-CGAN is defined by the generative-adversarial loss, the data loss function, and the total variation loss. Thus, the DD-CGAN can be trained more accurately. The discriminator is used to calculate the feature differences between the interpolated seismic data set and the complete seismic data set to drive the generator network for learning optimal parameters. The numerical results on the test data set and field seismic data set demonstrate the effectiveness of the proposed DD-CGAN.

Due to the huge differences between the unconventional shale and conventional sand reservoirs in many aspects such as the types and the characteristics of minerals, matrix pores and fluids, the construction of shale rock physics model is significant for the exploration and development of shale reservoirs. To make a better characterization of shale gas-bearing reservoirs, we first propose a new but more suitable rock physics model to characterize the reservoirs. We then use a well A to demonstrate the feasibility and reliability of the proposed rock physics model of shale gas-bearing reservoirs. Moreover, we propose a new brittleness indicator for the high-porosity and organic-rich shale gas-bearing reservoirs. Based on the parameter analysis using the constructed rock physics model, we finally compare the new brittleness indicator with the commonly used Young’s modulus in the content of quartz and organic matter, the matrix porosity, and the types of filled fluids. We also propose a new shale brittleness index by integrating the proposed new brittleness indicator and the Poisson’s ratio. Tests on real data sets demonstrate that the new brittleness indicator and index are more sensitive than the commonly used Young’s modulus and brittleness index for the high-porosity and high-brittleness shale gas-bearing reservoirs.