Search Results (122)

Perineural invasion (PNI) is a well-recognized histopathologic feature in multiple malignancies; however, its significance in breast cancer remains relatively underexplored. This review provides a synopsis of the current knowledge on PNI in breast cancer, discussing its histopathologic features, molecular mechanisms, diagnostic challenges, and clinical relevance. PNI is most frequently observed in high-grade invasive ductal carcinoma (IDC), particularly in triple-negative and HER2-positive subtypes. It is also seen in special histological subtypes such as mixed, metaplastic, and invasive micropapillary carcinomas. Mechanistically, PNI involves tumor–neural interactions, including neurotrophic factor signaling and epithelial–mesenchymal transition, contributing to tumor progression and potential locoregional recurrence (LRR). While PNI is linked to adverse prognosis in other tumors, its independent role remains unclear in breast cancer due to limited large-scale studies. Therefore, further investigation into its prognostic significance and potential therapeutic implications is needed. Future research should focus on refining diagnostic criteria and assessing targeted therapies to mitigate PNI-associated progression. This review summarizes the current knowledge on perineural invasion (PNI) in breast cancer, addressing its histological features, molecular mechanisms, diagnostic challenges, and clinical implications. Full article

Advanced oxidation processes (AOPs) are recognized as one of the most effective methods in the field of wastewater treatment, and the selection of catalysts in the oxidation process is very important. In the face of the traditional test trial-and-error method, the method of screening advanced oxidation catalysts is time-consuming and inefficient. This paper examines approximately two decades’ worth of literature pertaining to the development of catalysts facilitated by machine learning. A synopsis of the various advanced oxidation processes and reactive oxygen species (ROS) is provided. Subsequently, it is posited that the swift advancement of machine learning (ML) and its algorithmic classification has significantly propelled the progress in ML-assisted catalyst screening, active site prediction, the discovery of acceleration mechanisms, and catalyst structural research, which are subsequently elucidated. Despite ML’s proven efficacy as a tool within the domain of AOPs’ catalysis, the article concludes by presenting challenges and outlining future development strategies, particularly in light of issues pertaining to data quality and quantity, as well as inherent model limitations. Full article

As the global demand for surveillance cameras increases, the digital footage data also explicitly increases. Analyzing and extracting meaningful content from footage is a resource-depleting and laborious effort. The traditional video synopsis technique is used for constructing a small video by relocating the object in the time and space domains. However, it is computationally expensive, and the obtained synopsis suffers from jitter artifacts; thus, it cannot be hosted on a resource-constrained device. In this research, we propose a panoramic video synopsis framework to address and solve the problems of the efficient analysis of objects for better governance and storage. The surveillance system has multiple cameras sharing a common homography, which the proposed method leverages. The proposed method constructs a panorama by solving the broad viewpoints with significant deviations, collisions, and overlapping among the images. We embed a synopsis framework on the end device to reduce storage, networking, and computational costs. A neural network-based model stitches multiple camera feeds to obtain a panoramic structure from which only tubes with abnormal behavior were extracted and relocated in the space and time domains to construct a shorter video. Comparatively, the proposed model achieved a superior accuracy matching rate of 98.7% when stitching the images. The feature enhancement model also achieves better peak signal-to-noise ratio values, facilitating smooth synopsis construction. Full article

Water access and use impact land management decisions and livelihoods. Despite the integral role water plays in land systems, land system science (LSS) research often fails to explicitly incorporate water into analyses of socioecological systems (SES) resilience related to land. Nonetheless, water scarcity, especially in the face of climate change and resource degradation, is a pressing issue. Water availability is crucial to many ecosystem functions, from supporting biodiversity to mitigating extreme weather events such as flooding or drought. In this introduction to the “Water in Land System Science” Special Issue, we argue for deeper integration of land and water dynamics in LSS to increase SES resilience. First, we present an overview of the need for this integration, followed by a synopsis of the authored contributions in this Special Issue towards this goal. We then provide potential entry points researchers can use to foster this integration, exploring the following topics: water governance and hydrosocial territories, the cultural geographies of water, hydrophilia, water in agricultural transitions, remote sensing innovations, and participatory approaches to the study of the water component of land systems. We conclude that interactions between land, water, and people remain understudied, despite being more important than ever for ensuring future sustainability. Full article

Up until recently, research on loyalty and Islam—here considered as the discourses and practices of Muslims in regard to the Muslim tradition—had ignored the topic of loyalty. Interest in loyalty in Islam has just lately grown sufficiently and extensively. This entry is both bibliographical and thematic. It seeks to identify the principal themes that have dominated Muslim loyalty studies for the past thirty years or so. Additionally, it provides a thorough synopsis of over 100 studies on loyalty that were published during the same time span in Arabic and European languages. Allegiance in Muslim political ethics always had more than one connotation and the religious component of loyalty, while not strictly defined, allowed and even justified the overlap of multiple loyalties. A person’s or a family’s, ruler’s, or dynasty’s power to govern an area or defend religious institutions and symbols was intimately linked to the loyalty they could claim. Most studies agree on the diversity of political allegiance in modern Islam with regard to perceptions of religion, ethnicity, self-interest, etc.; it is also co-relative in the sense that it is mixed with other allegiances, such as those of family, tribe, leadership, or country. Full article

Ceramic proton conductors have the potential to lower the operating temperature of solid oxide cells (SOCs) to the intermediate temperature range of 400–600 °C. This is attributed to their superior ionic conductivity compared to oxide ion conductors under these conditions. However, prominent proton-conducting materials, such as yttrium-doped barium cerates and zirconates with specified compositions like BaCe_1−xY_xO_3−δ (BCY), BaZr_1−xY_xO_3−δ (BZY), and Ba(Ce,Zr)_1−yY_yO_3−δ (BCZY), face significant challenges in achieving dense electrolyte membranes. It is suggested that the incorporation of transition and alkali metal oxides as sintering additives can induce liquid phase sintering (LPS), offering an efficient method to facilitate the densification of these proton-conducting ceramics. However, current research underscores that incorporating these sintering additives may lead to adverse secondary effects on the ionic transport properties of these materials since the concentration and mobility of protonic defects in a perovskite are highly sensitive to symmetry change. Such a drop in ionic conductivity, specifically proton transference, can adversely affect the overall performance of cells. The extent of variation in the proton conductivity of the perovskite BCZY depends on the type and concentration of the sintering aid, the nature of the sintering aid precursors used, the incorporation technique, and the sintering profile. This review provides a synopsis of various potential sintering techniques, explores the influence of diverse sintering additives, and evaluates their effects on the densification, ionic transport, and electrochemical properties of BCZY. We also report the performance of most of these combinations in an actual test environment (fuel cell or electrolysis mode) and comparison with BCZY. Full article

Green hydrogen energy from electrocatalytic hydrogen evolution reactions (HERs) has gained much attention for its advantages of low carbon, high efficiency, interconnected energy medium, safety, and controllability. Non-precious metals have emerged as a research hotspot for replacing precious metal catalysts due to low cost and abundant reserves. However, maintaining the stability of non-precious metals under harsh conditions (e.g., strongly acidic, alkaline environments) remains a significant challenge. By leveraging the curling properties of two-dimensional materials, a new class of catalysts, encapsulating transition metal nanoparticles inside carbon (TM@C) chainmail, has been successfully developed. This catalyst can effectively isolate the active metal from direct contact with harsh reaction media, thereby delaying catalyst deactivation. Furthermore, the electronic structure of the carbon layer can be regulated through the transfer of electrons, which stimulates its catalytic activity. This addresses the issue of the insufficient stability of traditional non-precious metal catalysts. This review commences with a synopsis of the synthetic advancement of the engineering of TM@C chainmail catalysts. Thereafter, a critical discussion ensues regarding the electrocatalytic performance of TM@C chainmail catalysts during hydrogen production. Ultimately, a comprehensive review of the conformational relationship between the structure of TM@C chainmail catalysts and HER activity is provided, offering substantial support for the large-scale application of hydrogen energy. Full article

This paper investigates the potential of leveraging artificial intelligence to automate and optimize the verification process, particularly in generating System Verilog assertions for an Advance Peripheral Bus verification environment using Universal Verification Methodology. Generative artificial intelligence, such as ChatGPT, demonstrated its ability to produce accurate and valuable assertions by employing text-based prompts and image-fed inputs, significantly reducing the required manual effort. This research presents a way of generating System Verilog assertions using the ChatGPT prompt, presenting an image to the Large Language Models, and requesting the assertions needed for the respective protocol. This approach shows the potential for artificial intelligence to revolutionize functional verification by automating complex tasks, ultimately ensuring faster and more reliable System-on-Chip development. The assertions generated by the Large Language Models are integrated into an existing Advance Peripheral Bus verification environment. This process involves running the assertions on a free EDA Playground platform with all three simulators (Cadence Incisive, Mentor Questa, and Synopsys Verilog Compiler Simulator). The main conclusions are that using ChatGPT-4.0 for generating System Verilog assertions significantly reduces the time and effort required for functional verification, demonstrating its potential to enhance efficiency and accuracy in verifying complex System-on-Chip designs. Full article

With the ongoing obesity epidemic, the prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) is expected to rise and necessitates a greater understanding of how the disease proceeds from benign excess lipid in hepatocytes to liver fibrosis and eventually to liver cancer. MASLD is caused, at least in part, by hepatocytes’ storage of free fatty acids (FAs) that dysfunctional adipocytes are no longer able to store, and therefore, MASLD is a disease that involves both the liver and adipose tissues. The disease progression is not only facilitated by biochemical signals, but also by mechanical cues such as the increase in stiffness often seen with fibrotic fatty livers. The change in stiffness and accumulation of excess lipid droplets impact the ability of a cell to mechanosense and mechanotranduce, which perpetuates the disease. A mechanosensitive protein that is largely unexplored and could serve as a potential therapeutic target is the intermediate filament vimentin. In this review, we briefly summarize the recent research on hepatocyte and adipocyte mechanobiology and provide a synopsis of studies on the varied, and sometimes contradictory, roles of vimentin. This review is intended to benefit and encourage future studies on hepatocyte and adipocyte mechanobiology in the context of MASLD and obesity. Full article

Cutaneous wounds, both acute and chronic, begin with loss of the integrity, and thus barrier function, of the skin. Surgery and trauma produce acute wounds. There are 22 million surgical procedures per year in the United States alone, based on data from the American College of Surgeons, resulting in a prevalence of 6.67%. Acute traumatic wounds requiring repair total 8 million per year, 2.42% or 24.2 per 1000. The cost of wound care is increasing; it approached USD 100 billion for just Medicare in 2018. This burden for wound care will continue to rise with population aging, the increase in metabolic syndrome, and more elective surgeries. To heal a wound, an orchestrated, evolutionarily conserved, and complex series of events involving cellular and molecular agents at the local and systemic levels are necessary. The principal factors of this important function include elements from the neurological, cardiovascular, immune, nutritional, and endocrine systems. The objectives of this review are to provide clinicians engaged in wound care and basic science researchers interested in wound healing with an updated synopsis from recent publications. We also present data from our primary investigations, testing the hypothesis that cannabidiol can alter cutaneous wound healing and documenting their effects in wild type (C57/BL6) and db/db mice (Type 2 Diabetes Mellitus, T2DM). The focus is on the potential roles of the endocannabinoid system, cannabidiol, and the important immune-regulatory wound cytokine IL-33, a member of the IL-1 family, and connective tissue growth factor, CTGF, due to their roles in both normal and abnormal wound healing. We found an initial delay in the rate of wound closure in B6 mice with CBD, but this difference disappeared with time. CBD decreased IL-33 + cells in B6 by 70% while nearly increasing CTGF + cells in db/db mice by two folds from 18.6% to 38.8% (p < 0.05) using a dorsal wound model. We review the current literature on normal and abnormal wound healing, and document effects of CBD in B6 and db/db dorsal cutaneous wounds. CBD may have some beneficial effects in diabetic wounds. We applied 6–mm circular punch to create standard size full-thickness dorsal wounds in B6 and db/db mice. The experimental group received CBD while the control group got only vehicle. The outcome measures were rate of wound closure, wound cells expressing IL-33 and CTGF, and ILC profiles. In B6, the initial rate of wound closure was slower but there was no delay in the time to final closure, and cells expressing IL-33 was significantly reduced. CTGF + cells were higher in db/bd wounds treated with CBD. These data support the potential use of CBD to improve diabetic cutaneous wound healing. Full article

Lamiaceae is a botanical family rich in aromatic species that are in high demand such as basil, lavender, mint, oregano, sage, and thyme. It has great economical, ecological, ethnobotanical, and floristic importance. The aim of this work is to provide an updated view on the aerobiology of species from the family Lamiaceae, with an emphasis on novelties and emerging applications. From the aerobiology point of view, the greatest interest in this botanical family is related to the volatile organic compounds emitted by the plants and, to a much lesser extent, their pollen. Research has shown that the major volatile organic compounds emitted by the plants from this botanical family are monoterpenes and sesquiterpenes. The most important monoterpenes reported across studies include α-pinene, β-pinene, 1,8-cineole, menthol, limonene, and γ-terpinene. Most reports tend to cover species from the subfamily Nepetoideae. Volatile oils are produced by glandular trichomes found on aerial organs. Based on general morphology, two main types are found in the family Lamiaceae, namely peltate and capitate trichomes. As a result of pollinator-mediated transfer of pollen, Lamiaceae species present a reduced number of stamens and quantity of pollen. This might explain the low probability of pollen presence in the air from these species. A preliminary synopsis of the experimental evidence presented in this work suggests that the interplay of the organic particles and molecules released by these plants and their environment could be leveraged for beneficial outcomes in agriculture and landscaping. Emerging reports propose their use for intercropping to ensure the success of fructification, increased yield of entomophilous crops, as well as in sensory gardens due to the therapeutic effect of volatiles. Full article

One of the United Nations’ 17 Sustainable Development Goals is to “Ensure access to affordable, sustainable, and clean energy for all.” Additionally, the growing concerns about climate change and energy security have heightened the importance of exploring alternative energy sources to replace fossil fuels. The utilisation of agricultural waste for bioenergy production has acquired significant attention due to its potential to mitigate environmental impacts and provide renewable energy sources. However, the major obstacle to producing bioenergy is managing the supply chain while considering economic, environmental, and social factors in an optimal way. This paper presents a comprehensive overview of the literature on the management of agriculture waste supply chains, specifically related to the use of modelling and optimisation techniques for planning. The first section describes different stages of the supply chain and various technologies for converting biomass to bioenergy. This is followed by a synopsis of the literature reviewed based on decision levels, objective functions, modelling methodologies, and optimisation approaches. Finally, the review highlights limitations and gaps in current research and the areas with potential for further exploration. Full article

In recent years, the scientific and technological developments have led to an explosion of available videos on the web, increasing the necessity of fast and effective video analysis and summarization. Video summarization methods aim to generate a synopsis by selecting the most informative parts of the video content. The user’s personal preferences, often involved in the expected results, should be taken into account in the video summaries. In this paper, we provide the first comprehensive survey on personalized video summarization relevant to the techniques and datasets used. In this context, we classify and review personalized video summary techniques based on the type of personalized summary, on the criteria, on the video domain, on the source of information, on the time of summarization, and on the machine learning technique. Depending on the type of methodology used by the personalized video summarization techniques for the summary production process, we classify the techniques into five major categories, which are feature-based video summarization, keyframe selection, shot selection-based approach, video summarization using trajectory analysis, and personalized video summarization using clustering. We also compare personalized video summarization methods and present 37 datasets used to evaluate personalized video summarization methods. Finally, we analyze opportunities and challenges in the field and suggest innovative research lines. Full article

This review focuses on an extensive synopsis of the recent improvements in CO₂ hydrogenation over structured zeolites, including their properties, synthesis methods, and characterization. Key features such as bimodal mesoporous structures, surface oxygen vacancies, and the Si/Al ratio are explored for their roles in enhancing catalytic activity. Additionally, the impact of porosity, thermal stability, and structural integrity on the performance of zeolites, as well as their interactions with electrical and plasma environments, are discussed in detail. The synthesis of structured zeolites is analyzed by comparing the advantages and limitations of bottom-up methods, including hard templating, soft templating, and non-templating approaches, to top-down methods, such as dealumination, desilication, and recrystallization. The review addresses the challenges associated with these synthesis techniques, such as pore-induced diffusion limitations, morphological constraints, and maintaining crystal integrity, highlighting the need for innovative solutions and optimization strategies. Advanced characterization techniques are emphasized as essential for understanding the catalytic mechanisms and dynamic behaviors of zeolites, thereby facilitating further research into their efficient and effective use. The study concludes by underscoring the importance of continued research to refine synthesis and characterization methods, which is crucial for optimizing catalytic activity in CO₂ hydrogenation. This effort is important for achieving selective catalysis and is paramount to the global initiative to reduce carbon emissions and address climate change. Full article

Ovarian cancer is the deadliest gynecologic malignancy. The majority of patients diagnosed with advanced ovarian cancer will relapse, at which point additional therapies can be administered but, for the most part, these are not curative. As such, a need exists for the development of novel therapeutic options for ovarian cancer patients. Research in the field of targeted protein degradation (TPD) through the use of proteolysis-targeting chimeras (PROTACs) has significantly increased in recent years. The ability of PROTACs to target proteins of interest (POI) for degradation, overcoming limitations such as the incomplete inhibition of POI function and the development of resistance seen with other inhibitors, is of particular interest in cancer research, including ovarian cancer research. This review provides a synopsis of PROTACs tested in ovarian cancer models and highlights PROTACs characterized in other types of cancers with potential high utility in ovarian cancer. Finally, we discuss methods that will help to enable the selective delivery of PROTACs to ovarian cancer and improve the pharmacodynamic properties of these agents. Full article