Underground pipelines serve as critical infrastructure for gas transmission, strategically buried for safety, environmental, and economic considerations. Despite their importance, operational challenges and external interferences can lead to underground gas leaks with potentially catastrophic consequences for both human safety and the environment. The presence of a protective soil bed introduces complexities in understanding subsurface transport phenomena and quantifying gas releases accurately. Herein, this review presents a systematic analysis of published research in the field of underground gas releases, with an emphasis on interdisciplinary approaches that connect the lithosphere and atmosphere. The analysis highlights the broad spectrum of employed methods, including theoretical models based on fundamental principles, empirical formulations derived from experimental data, and sophisticated computational tools. A clear fundamental understanding and computational analysis, and to a lesser extent experimental, have been established to describe the migration regime. In contrast, more empirical research has addressed the crater formation regime, though focus was given to the far-field modelling following the soil ejection rather than the transient phenomena leading to the formation of the crater. Additionally, this review touches upon practical and conceptual topics, such as detection and localization techniques, and flow regimes in other gaseous flows through soil and powder beds, putting into question the applicability of some presumed granulated concepts to the flowing behavior expected beyond migration. The research landscape predominantly focuses on investigating the influence of release parameters on the release phenomena only from the atmospheric or soil domain perspective. This work provides insights that aim to first transcend both domains and then bridge the three distinct flow regimes-migration, uplift, and crater formation-despite the limited acknowledgment of the necessity of addressing all regimes concurrently through a universal approach. This review serves as a valuable resource for engineers to develop innovative solutions for the management of risks associated with underground gas leaks.

As the world recovers from the COVID-19 pandemic, a resurgence in MPXV cases is causing serious concern. The early clinical similarity of MPXV to common ailments like the flu and cold, coupled with the resemblances of its progressing rash to other infections, underscores the importance of prompt and accurate diagnosis. Among the infections, smallpox is clinically closest to MPXV, and rashes similar to MPXV stages also appear in syphilis and varicella zoster. A comprehensive review of MPXV, herpes, and syphilis was carried out, including structural and morphological features, origins, transmission modes, and computational studies. PubMed literature search on MPXV, using MeSH key terms, yielded 1904 results, with the analysis revealing prominent links to sexually transmitted diseases. More in-depth exploration of MPXV, Herpes Simplex Virus (HSV), and Syphilis revealed further disease interconnections and geographical correlations. These findings emphasize the need for a holistic understanding of these interconnected infectious agents for better control and management.

Normal axon development depends on the action of mechanical forces both generated within the cytoskeleton and outside the cell, but forces of large magnitude or rate cause damage instead. Computational models aid scientists in studying the role of mechanical forces in axon growth and damage. These studies use simulations to evaluate how different sources of force generation within the cytoskeleton interact with each other to regulate axon elongation and retraction. Furthermore, mathematical models can help optimize externally applied tension to promote axon growth without causing damage. Finally, scientists also use simulations of axon damage to investigate how forces are distributed among different components of the axon and how the tissue surrounding an axon influences its susceptibility to injury. In this review, we discuss how computational studies complement experimental studies in the areas of axon growth, regeneration, and damage.

The new pandemic caused by the coronavirus (SARS-CoV-2) has become the biggest challenge that the world is facing today. It has been creating a devastating global crisis, causing countless deaths and great panic. The search for an effective treatment remains a global challenge owing to controversies related to available vaccines. A great research effort (clinical, experimental, and computational) has emerged in response to this pandemic, and more than 125000 research reports have been published in relation to COVID-19. The majority of them focused on the discovery of novel drug candidates or repurposing of existing drugs through computational approaches that significantly speed up drug discovery. Among the different used targets, the SARS-CoV-2 main protease (Mpro), which plays an essential role in coronavirus replication, has become the preferred target for computational studies. In this review, we examine a representative set of computational studies that use the Mpro as a target for the discovery of small-molecule inhibitors of COVID-19. They will be divided into two main groups, structure-based and ligand-based methods, and each one will be subdivided according to the strategies used in the research. From our point of view, the use of combined strategies could enhance the possibilities of success in the future, permitting to development of more rigorous computational studies in future efforts to combat current and future pandemics.

The aim of this review is to highlight and provide an update on the current development of pesticide remediation methods, focusing on the utilization of different cyclodextrin (CD) molecules. Because of less environmental impact and non-toxic nature, CDs are beneficial for pesticide remediation, reducing environmental risk and health hazards. They are advantageous for the removal of pesticides from contaminated areas, as well as for better pesticide formulation and, posing significant effects on the hydrolysis or degradation of pesticides. The review focuses on the current trend and innovations regarding the methods and strategies employed for using CDs in designing pesticide remediation. Nowadays, in addition to the conventional experimental techniques, molecular simulation approaches are significantly contributing to the study of such phenomena and hence are recognized as a widely used tool.

Computational frameworks have been under specific attention within the last two decades. Molecular Dynamics (MD) simulations, identical to the other computational approaches, try to address the unknown question, lighten the dark areas of unanswered questions, to achieve probable explanations and solutions. Owing to their complex microporous structure on one side and the intricate biochemical nature of various materials used in the structure, separative membrane materials possess peculiar degrees of complications. More notably, as nanocomposite materials are often integrated into separative membranes, thin-film nanocomposites and porous separative nanocomposite materials could possess an additional level of complexity with regard to the nanoscale interactions brought to the structure. This critical review intends to cover the recent methods used to assess membranes and membrane materials. Incorporation of MD in membrane technology-related fields such as desalination, fuel cell-based energy production, blood purification through hemodialysis, etc., were briefly covered. Accordingly, this review could be used to understand the current extent of MD applications for separative membranes. The review could also be used as a guideline to use the proper MD implementation within the related fields.

Hallucinations can occur in different sensory modalities, both simultaneously and serially in time. They have typically been studied in clinical populations as phenomena occurring in a single sensory modality. Hallucinatory experiences occurring in multiple sensory systems-multimodal hallucinations (MMHs)-are more prevalent than previously thought and may have greater adverse impact than unimodal ones, but they remain relatively underresearched. Here, we review and discuss: (1) the definition and categorization of both serial and simultaneous MMHs, (2) available assessment tools and how they can be improved, and (3) the explanatory power that current hallucination theories have for MMHs. Overall, we suggest that current models need to be updated or developed to account for MMHs and to inform research into the underlying processes of such hallucinatory phenomena. We make recommendations for future research and for clinical practice, including the need for service user involvement and for better assessment tools that can reliably measure MMHs and distinguish them from other related phenomena.

microRNAs are small, noncoding RNA that negatively regulate gene expression. Since their discovery in 1993, approximately 2500 human mature microRNAs have been discovered and details of their biogenesis, mechanism of action, and function has been studied. Aberrant expression of microRNAs has since been observed in numerous disease states particularly cancer, neurologic disorders, autoimmune diseases, metabolic diseases and cardiovascular diseases. Because of this, a strong interest in developing novel therapies that modulate microRNA function has emerged. Although, several strategies have been employed, small molecule drugs have shown great promise due their inherent stability, bioavailability, and cost-efficiency. In this review, we discuss the microRNA modulating small molecules that have thus far been identified in the literature and highlight the need for continued research in this field.

Mathematical transmission models are increasingly used to guide public health interventions for infectious diseases, particularly in the context of emerging pathogens; however, the contribution of modeling to the growing issue of antimicrobial resistance (AMR) remains unclear. Here, we systematically evaluate publications on population-level transmission models of AMR over a recent period (2006-2016) to gauge the state of research and identify gaps warranting further work.
We performed a systematic literature search of relevant databases to identify transmission studies of AMR in viral, bacterial, and parasitic disease systems. We analyzed the temporal, geographic, and subject matter trends, described the predominant medical and behavioral interventions studied, and identified central findings relating to key pathogens.
We identified 273 modeling studies; the majority of which (> 70%) focused on 5 infectious diseases (human immunodeficiency virus (HIV), influenza virus, Plasmodium falciparum (malaria), Mycobacterium tuberculosis (TB), and methicillin-resistant Staphylococcus aureus (MRSA)). AMR studies of influenza and nosocomial pathogens were mainly set in industrialized nations, while HIV, TB, and malaria studies were heavily skewed towards developing countries. The majority of articles focused on AMR exclusively in humans (89%), either in community (58%) or healthcare (27%) settings. Model systems were largely compartmental (76%) and deterministic (66%). Only 43% of models were calibrated against epidemiological data, and few were validated against out-of-sample datasets (14%). The interventions considered were primarily the impact of different drug regimens, hygiene and infection control measures, screening, and diagnostics, while few studies addressed de novo resistance, vaccination strategies, economic, or behavioral changes to reduce antibiotic use in humans and animals.
The AMR modeling literature concentrates on disease systems where resistance has been long-established, while few studies pro-actively address recent rise in resistance in new pathogens or explore upstream strategies to reduce overall antibiotic consumption. Notable gaps include research on emerging resistance in Enterobacteriaceae and Neisseria gonorrhoeae; AMR transmission at the animal-human interface, particularly in agricultural and veterinary settings; transmission between hospitals and the community; the role of environmental factors in AMR transmission; and the potential of vaccines to combat AMR.

A defining hallmark of cancer is aberrant cell proliferation. Efforts to understand the generative properties of cancer cells span all biological scales: from genetic deviations and alterations of metabolic pathways to physical stresses due to overcrowding, as well as the effects of therapeutics and the immune system. While these factors have long been studied in the laboratory, mathematical and computational techniques are being increasingly applied to help understand and forecast tumor growth and treatment response. Advantages of mathematical modeling of proliferation include the ability to simulate and predict the spatiotemporal development of tumors across multiple experimental scales. Central to proliferation modeling is the incorporation of available biological data and validation with experimental data. Areas covered: We present an overview of past and current mathematical strategies directed at understanding tumor cell proliferation. We identify areas for mathematical development as motivated by available experimental and clinical evidence, with a particular emphasis on emerging, non-invasive imaging technologies. Expert commentary: The data required to legitimize mathematical models are often difficult or (currently) impossible to obtain. We suggest areas for further investigation to establish mathematical models that more effectively utilize available data to make informed predictions on tumor cell proliferation.