Cases of road cave-ins have been reportedly increasing globally and reports have associated this phenomenon to underground soil erosion due to defective sewer pipes. As the sewer pipes age, they may develop some defects which may lead to cracks and crevices that will lead to infiltration of the soils surrounding the pipe into the pipe, leading to the formation of cavities around the pipe. Therefore, this study investigated the factors behind the causes of underground soil erosion due to defective sewer pipes and proffered solutions for combating underground soil erosion due to defective sewer pipes. The study objective included; (a) establishing how the soil particle sizes affect the internal soil erosion due to defective sewer pipes, (b) determination of the effect of defect sizes on the internal soil erosion due to defective sewer pipes, (c) establishing the effect of the embedment material used on the internal soil erosion due to defective sewer pipes, (d) investigation of the type of soil erosion mechanism in the presence of a buried sewer pipe defect caused by the groundwater infiltration process. The methodology of the study involved reviewing and analyzing secondary qualitative and quantitative data. The findings established that the defect size of the pipe, the type and characteristics of the soil and the type of embedment materials used affected erosion of soil around a defective sewer pipe.

Cancer is a complex and devastating disease that has engaged scientists and researchers for decades. Despite tremendous efforts, previous hypotheses about cancer development have not achieved significant breakthroughs. Evolutionary Cancer Cell Biology (ECCB) is a novel and emerging branch of oncological science that provides an evolutionary perspective on the origin of cancer. It reveals that the cancer genome evolved hundreds of millions of years ago, long before multicellular organisms such as metazoans and humans emerged. ECCB aims to unify all evolutionary insights, hypotheses, and theories into a cohesive framework. It investigates the intricate relationship between cancer genomics and ancient pre-metazoan genes that emerge when normal cells transform into cancer cells. It challenges the conventional wisdom of cancer research by suggesting that cancer could arise through intrinsic cellular mechanisms without genetic alterations and mutations. Furthermore, it postulates that somatic mutations are only secondary, downstream events in the process of oncogenesis.

Chikungunya virus (CHIKV) is a mosquito borne RNA virus that poses an emerging threat to humans. As other RNA viruses, CHIKV encodes an error-prone RNA polymerase which, in addition to full-length genomes, gives rise to truncated, non-functional genomes coined defective viral genomes (DVGs). DVGs have been intensively studied in the context of therapy, as they can inhibit viral replication and dissemination in their hosts. In this work, we interrogate the influence of viral RNA secondary structures on the production of CHIKV DVGs. We experimentally map RNA secondary structures of CHIKV genome using selective 2′-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP), which couples chemical labelling with next-generation sequencing. We correlate the inferred secondary structure with preferred deletion sites of CHIKV DVGs. We document an increased probability of DVG generation with truncations at unpaired nucleotides within the secondary structure. We then generated a CHIKV mutant bearing synonymous changes at the nucleotide level to disrupt existing RNA secondary structure (CHIKV-D2S). We show that CHIKV-D2S presents altered DVG generation compared to wild-type virus, correlating with its change in RNA secondary structure obtained by SHAPE-MaP. Our work thus demonstrates that RNA secondary structure impacts CHIKV DVG production during replication.

The success of many viruses depends upon cooperative interactions between viral genomes. For example, viruses that coinfect the same cell can share essential gene products, such as replicase, the enzyme that replicates the viral genome. However, when cooperation occurs, there is the potential for ‘cheats’ to exploit that cooperation. We suggest that: (1) the biology of viruses makes viral cooperation particularly susceptible to cheating; (2) cheats are common across a wide range of viruses, including viral entities that are already well studied, such as defective interfering genomes, and satellite viruses. Consequently, evolutionary theory developed to explain cheating offers a conceptual framework for understanding and manipulating viral dynamics. At the same time, viruses offer unique opportunities to study how cheats evolve, because cheating is relatively common in viruses, compared with taxa where cooperation is more usually studied, such as animals.

Mice are not natural hosts for influenza A viruses (IAVs), but they are useful models for studying antiviral immune responses and pathogenesis. Serial passage of IAV in mice invariably causes the emergence of adaptive mutations and increased virulence. Typically, mouse-adaptation studies are conducted in inbred laboratory strains BALB/c and C57BL/6, which have defects in the antiviral Mx1 gene that results in increased susceptibility to infection and disease severity. Here, we report the adaptation of IAV reference strain A/California/07/2009(H1N1) (a.k.a. CA/07) in outbred Swiss Webster mice. Serial passage led to increased virulence and lung titers, and dissemination of the virus to brains. We adapted a deep-sequencing protocol to identify and enumerate adaptive mutations across all genome segments. Among mutations that emerged during mouse-adaptation, we focused on amino acid substitutions in polymerase subunits: polymerase basic-1 (PB1) T156A and F740L, and polymerase acidic (PA) E349G. These mutations were evaluated singly and in combination in minigenome replicon assays, which revealed that PA E349G increased polymerase activity. By selectively engineering these three adaptive PB1 and PA mutations into the parental CA/07 strain, we demonstrated that adaptive mutations in polymerase subunits decreased the production of defective viral genome segments with internal deletions, and dramatically increased the release of infectious virions from mouse cells. Together, these findings increase our understanding of the contribution of polymerase subunits to successful host adaptation.

The generation of different types of defective viral genomes (DVG) is an unavoidable consequence of the error-prone replication of RNA viruses. In recent years, a particular class of DVGs, those containing long deletions or genome rearrangements, has gain interest due to their potential therapeutic and biotechnological applications. Identifying such DVGs in high-throughput sequencing data has become an interesting computational problem. Up to nowadays, several algorithms have been proposed, though all incur in false positives, a problem of practical interest if such DVGs have to be synthetized and tested in the laboratory. Here we develop a novel software, DVGfinder, that wraps the two most commonly used algorithms into a pipeline that predicts DVGs. Using a gradient boosting classifier machine learning algorithm, we evaluate the performance of DVGfinder compared to previous algorithms and found that it outcompetes their precision and sensitivity in simulated datasets. DVGfinder generates user-friendly output files in HTML format that can assist users to identify DVGs based on their associated probability of being true positives.

A series of defective ZSM-5 zeolites (~300 nm, SiO₂/Al₂O₃ ratio of 55, 100, 400 and 950) were intentionally prepared and systematically studied by XRD, SEM, ²⁹Si MAS NMR, argon physisorption, NH₃-TPD and FT-IR technologies. The nature, the amount and the accessibility of the acid sites of defective ZSM-5 zeolites are greatly different from reported ZSM-5 zeolites with perfect crystal structure. The co-existed strong Brønsted acid sites (Si(OH)Al) and weak Brønsted acid sites (hydroxyl nests) over defective ZSM-5 zeolites might lead to unique catalytic function. Zn(C₂H₅)₂ was grafted onto defective ZSM-5 zeolites through chemical liquid deposition (CLD) method. Interestingly, FT-IR spectroscopy studies find that Zn(C₂H₅)₂ was preferentially grafted on the hydroxyl nests with weak acidity rather than the Si(OH)Al groups with strong acidity over different defective ZSM-5 zeolites. Particularly, home-built operando dual beam FTIR-MS was applied to study the catalytic performance of Zn species locating at different sites of defective ZSM-5 zeolites under n-hexane transformation. Results show that Zn species grafted over hydroxyl nests obtain better dehydrogenation performance than Zn species over framework aluminum. This study provides guidance for the rational design of highly efficient alkane dehydrogenative aromatization catalysts.