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Background: Diabetes mellitus and Alzheimer’s disease are two common diseases that majorly affect the elderly population. Patients in both cases are increasing day by day. They are considered two independent diseases, but recent evidence suggests that they have a lot in common. Objective: In this review, we focused on the connection between Alzheimer's disease and diabetes and highlighted the importance of antidiabetic drugs against Alzheimer's disease. Methods: Common pathways such as obesity, vascular diseases, oxidative stress, mitochondrial dysfunction, mutation of the ApoE4 gene, and Sirtuin gene were found to manipulate both diseases. Antidiabetic drugs are found to have promising effects on Alzheimer’s disease, acting by reducing insulin resistance, neuronal protection, and reducing amyloid-beta plaques. Some anti-diabetic drugs have shown promising results in vivo and in vitro studies. Results: No review present focuses on the structural features of the antidiabetic molecules against Alzheimer’s disease, their crosslinking pathophysiology, the role of natural bioactive molecules, in silico advancements followed by preclinical and clinical studies, and current advancements. Hence, we concentrated on the factors mentioned in the objectives. Conclusion: Alzheimer's disease can be considered a form of 'type-3 diabetes,' and repurposing the anti-diabetic drug will open up new paths of research in the field of Alzheimer's disease drug discovery.

A multilevel lockdown was introduced during the COVID-19 pandemic worldwide. This new experience, however, received mixed responses from the public in different countries including India. A quantitative self-report, the Pro-Lockdown Compliance Scale (Pro-LCS), was developed to help 1) the Government and enforcing agents understand the compliance level of the public and 2) researchers investigate the antecedent factors of the compliance of the lockdown measures. The initial 10 items were administered to 309 male residents in Kerala via an online survey. The responses were randomly divided and submitted to exploratory and confirmatory factor analyses. Both analyses consistently support that the scale is best represented by a 5-item unidimensional model. Moreover, the Pro-LBS also demonstrated adequate internal consistency. The preliminary findings suggest that the scale is a brief and useful tool to examine the compliance level of the lockdown measures.

Bacterial leaf blight (BLB) is one of the major rice diseases in Malaysia. This disease causes substantial yield loss as high as 70%. Development of rice varieties which inherited BLB resistant traits is a crucial approach to promote and sustain rice industry in Malaysia. Hence, this study aims were to enhance BLB disease resistant characters of high yielding commercial variety MR219 through backcross breeding approach with supporting tool of marker-assisted selection (MAS). Broad spectrum BLB resistance gene, Xa7 from donor parent IRBB7 were introgressed into the susceptible MR219 (recurrent parent) using two flanking markers ID7 and ID15. At BC3F4, we managed to generate 19 introgressed lines with homozygous Xa7 gene and showed resistant characteristics as donor parent when it was challenged with Xanthomonas oryzae pv. oryzae through artificial inoculation. Recurrent parent MR219 and control variety, MR263 were found to be severely infected by the disease. The improved lines exhibited similar morphological and yield performance characters as to the elite variety, MR219. Two lines, PB-2-107 and PB-2-34 were chosen to be potential lines because of their outstanding performances compared to parent, MR219. This study demonstrates a success story of MAS application in development of improved disease resistance lines of rice against BLB disease. Resumo A mancha bacteriana das folhas (BLB) é uma das principais doenças do arroz na Malásia. Essa doença causa perdas substanciais de rendimento de até 70%. O desenvolvimento de variedades de arroz que herdaram características de resistência ao BLB é uma abordagem crucial para promover e sustentar a indústria do arroz na Malásia. Portanto, o objetivo deste estudo foi aumentar os caracteres BLB resistentes a doenças da variedade comercial MR219 de alto rendimento por meio de uma abordagem de cruzamento retrocruzamento com ferramenta de apoio de seleção assistida por marcador (MAS). O gene de resistência a BLB de amplo espectro, Xa7 do pai doador IRBB7, foi introgressado no MR219 suscetível (pai recorrente) usando dois marcadores flanqueadores ID7 e ID15. No BC3F4, conseguimos gerar 19 linhagens introgressadas com o gene Xa7 homozigoto e apresentamos características de resistência como genitor doador quando desafiado com Xanthomonas oryzae pv. oryzae por inoculação artificial. O pai recorrente MR219 e a variedade controle, MR263, estavam gravemente infectados pela doença. As linhas melhoradas exibiram características morfológicas e de desempenho de rendimento semelhantes às da variedade elite, MR219. Duas linhas, PB-2-107 e PB-2-34, foram escolhidas como linhas potenciais por causa de seus desempenhos excelentes em comparação com a mãe, MR219. Este estudo demonstra uma história de sucesso de aplicação de MAS no desenvolvimento de linhas de arroz melhoradas com resistência a doenças contra a doença BLB.

We studied the outcome of glycaemic management using Diahome, a smart-phone application compared to conventional treatment. Overall acceptability of the application among users was also assessed.This is a retrospective, case-control study of patients on virtual diabetes care using the Diahome app (n = 441) and those visited the hospital out-patient services (n = 446) between April and June 2021. Men and women aged 45-60 years with type 2 diabetes (T2DM) were selected.A total of 173 records with initial and follow-up visits were analyzed (app users n = 91, non-app users n = 82). Participants were aged 59 ± 12 years and were obese. The two groups were similar by age, gender distribution and duration of T2DM. Fasting blood glucose significantly reduced only among the app-users from a baseline level of 156 ± 70 mg/dl to 129 ± 40 mg/dl at follow-up (p 0.02). Reduction in HbA1c levels was observed in both groups (p 0.0001); percentage improvement was better among app (15.8%) than in non-app users (10.4%), p = 0.004. Triglycerides level were higher at both time points among app-users (p 0.05) as compared to the other group. More than 56% of the users rated the performance of Diahome app as excellent; virtual consultation was rated the highest (71.5%) among the Diahome services.Glycaemic management of diabetes using a dedicated mobile application was superior to in-person hospital visits. Its long-term effectiveness and cost savings need to be ascertained.

The aerospace industry is constantly experimenting with innovative technologies to improve efficiency, effectiveness and sustainability. The use of superconducting machines emerged as a promising solution to address the growing demands of Aerospace applications. Superconducting machines offer significant advantages such as higher power density, reduced weight and improved efficiency compared to conventional electrical machines. However, efficient cooling methods are critical to maintain superconducting materials at low-temperature operating conditions. This abstract provides a comprehensive overview of superconducting machines and their associated cooling systems designed for space applications. A superconducting machine uses high-temperature superconductors to achieve near-zero electrical resistance, enabling high currents to be transmitted with low energy losses. This feature allows development of lightweight and compact electric propulsion systems contribute to improved fuel efficiency and extended mission capabilities in space vehicles. A cooling system is an important component of a superconducting machine because it ensures that the superconducting materials remain below their critical temperature. Various cooling techniques are being explored, including cryogenic cooling, liquid nitrogen cooling, and cryocoolers. These cooling systems effectively extract the heat generated during engine operation, maintaining the superconducting components in their superconducting state.

This article offers a thorough review of shape memory alloys' (SMAs') uses in the Space research field. The utility of SMAs in a variety of applications, including morphing wings (using both experimental and modelling methods), customising orientation and inlet shapes for various propulsion systems, implementing flexible chevrons to improve thrust while lowering noise, and reducing overall power consumption, is the main topic of this paper. The use of SMAs in applications in space is also covered in the paper, including how they may be used to create low-shock launchers, isolate micro-vibrations, and enable self-deployable solar sails. The essay also emphasises the novel structures and tools made possible by SMAs. One noteworthy method covered in the article is putting SMA wires in the laminate's midplane and embedding them into the fabric a layer of composite laminates. When compared to traditional composite constructions, the incorporation of SMAs into composite has shown better damage resistance and ductility. The reaction of a bright hybrid plastic composite plates to a very low-velocity impact is examined experimentally and numerically in this paper, which highlights the benefits of inserting SMA wires. Among these benefits are improved damage resistance, better ductility, higher composite hardness, and increased energy absorption before failure. Shape memory alloy (SMA) are the subject of extensive industrial applications and ongoing study in the field of materials. Its two distinguishing qualities, the shape memory impact and superelasticity, are mostly to blame for this. A composition's structure that suffered a phase transition as a result of temperatures, pressures, mechanical forces, and other factors is implies to as having a "shape memory effect". The composition, despite the very significant plastic deformation to which its surface is susceptible to, may recover to its original form under the influence of temperature as well as other factors.

The Immense growth in the implementation of electric vehicles (EVs), has established a path in the advancements of charging infrastructure. Interlinking and connecting the charging stations to a common server is essential for future EV adoption, and this can reduce the user's anxiety. The existing charging stations have not implemented charging slot availability and time scheduling management. The objective of this research is to enhance the current electric vehicle (EV) charging infrastructure by gathering and sharing real-time information about the availability of reserve slots at charging stations. This information is made available to users through an interactive application created with Android Studio, allowing them to locate the closest charging station for their EV. The application utilizes the State of Charge of the EV to assign available charging slots. The proposed real-time predictive charging server infrastructure avoids latency, effectively manages time scheduling, and avoids draining electric vehicle batteries. This proposed system uses the real-time traffic database to estimate the minimum distance path to reach the charging station. The system utilizes soil moisture sensors, Potassium, sodium and phosphorus sensors, and amount of water needed for crops. The system is designed to be energy-efficient, cost-effective, and easy to use. It can be remotely controlled and monitored via a mobile application, allowing farmers to have real-time access to their irrigation systems. This system has the potential to improve crop yields, conserve water resources, and reduce labor costs associated with manual irrigation practices.

The aerospace industry relies heavily on the structural integrity and performance of aircraft to ensure safe and efficient operations. Over time, aircraft structures can experience wear, corrosion or damage due to various factors such as environmental conditions, fatigue or accidents. Structural repairs are necessary to maintain the airworthiness of aircraft and extend their operational life. These brief highlights the importance of coating solutions in structural repair for aerospace. Coatings play an important role in protecting aircraft structures from degradation, preventing further damage and restoring their mechanical properties. In addition, coatings can improve aerodynamic performance, improve fuel efficiency and reduce maintenance costs. The brief discusses the various types of coating solutions used in aeronautical structural repair. These include corrosion-resistant coatings, abrasion-resistant coatings, heat-resistant coatings, and composite bonding systems. Each type of coating serves a specific purpose in mitigating structural damage and restoring the structural integrity of aircraft components. Also, the brief explores the key properties and characteristics of effective coating solutions. These properties include adhesive strength, flexibility, durability, weight considerations, chemical resistance, and thermal stability. Understanding these properties is critical to selecting the appropriate coating solution for specific repair applications. Also summarizes the challenges and considerations associated with coating applications in aerospace structural repair. These challenges include surface preparation, application techniques, curing processes, compatibility with existing coatings and compliance with regulatory requirements. Overcoming these challenges is essential to ensure the successful implementation of coating solutions in structural repair operations. Finally, the abstract discusses emerging trends and developments in aeronautical structural repair coating technologies. These include eco-friendly coatings, self-healing coatings, nano-coatings and smart coatings with sensing capabilities. These developments hold promise for improving the effectiveness and efficiency of structural repair processes in the aerospace industry.

Tensile stress combined with exposure to a corrosive environment result in a cracking process known as stress corrosion cracking (SCC). It falls in the threshold of the material's fatigue limit and dry cracking. Tensile stress can be applied directly or exist as residual stress within the material. SCC results from specific combinations of composition, environment, and stress. Processes like cold forming, welding, heat treating, machining, and grinding introduce residual stresses. Stress erosion cracking (SCC) occurs when cracks form under static tensile stress and the environment around us . It develops by the result of the interaction between mechanical stress and corrosion/oxidation reactions. The occurrence and progression of SCC depend on the materials, applied loads, and environmental conditions. Some Contributing Factors to SCC In summary, two main features of SCC are emphasized: localization and acceleration of oxidative reactions.

Background: Hair loss, or alopecia, is a common disorder that affects between 0.2-2% of the world's population and have significant impacts on a person's mental and physical health. Normal hair loss on a healthy head is between 50 and 100 hairs a day. Alopecia is a disorder in which the follicles in certain people start losing hair prematurely because they are not healthy, increasing the pace at which hair falls. Alopecia can be caused by poor nutrition, chronic stress, genetics, or other factors, and there are several types, each with a unique cause and symptom. Apart from improving quality of life, using methods like hair treatments or transplants, many homeopathic herbal ingredients are reported useful in managing alopecia and hair fall. This study was aimed to investigate the effectiveness of a formulation Zauberӧl® containing Arnica montana, Ceanothus americanus, Eclipta prostrata, Hibiscus Rosa sinensis, Jaborandi, Murraya koenigii, Sabal serrulata & Thuja occidentalis in testosterone-induced alopecia in Wistar rats.

It was found recently that the durability of Ni‒Co dispersed on a samaria-doped ceria (SDC) hydrogen electrode was improved remarkably via reversible cycling operation between steam electrolysis and fuel cell-modes. The microstructure was observed to be stabilized, with certainty, due to a strong interaction between Ni‒Co and SDC. Aiming to develop a durable, practical hydrogen electrode with such a stabilized microstructure, we prepared new Ni–SDC H2 electrodes by a convenient protocol by the use of Ni nanoparticles with uniform size. The initial performance of the Ni–SDC H2 electrode thus prepared was comparable or slightly higher than that of our Ni‒Co dispersed SDC electrode prepared by an impregnation method.

BACKGROUND: Tuberculosis (TB) is a highly infectious disease that mainly affects the human lungs. The gold standard for TB diagnosis is Xpert Mycobacterium tuberculosis/ resistance to rifampicin (MTB/RIF) testing. X-ray, a relatively inexpensive and widely used imaging modality, can be employed as an alternative for early diagnosis of the disease. Computer-aided techniques can be used to assist radiologists in interpreting X-ray images, which can improve the ease and accuracy of diagnosis. OBJECTIVE: To develop a computer-aided technique for the diagnosis of TB from X-ray images using deep learning techniques. METHODS: This research paper presents a novel approach for TB diagnosis from X-ray using deep learning methods. The proposed method uses an ensemble of two pre-trained neural networks, namely EfficientnetB0 and Densenet201, for feature extraction. The features extracted using two CNNs are expected to generate more accurate and representative features than a single CNN. A custom-built artificial neural network (ANN) called PatternNet with two hidden layers is utilized to classify the extracted features. RESULTS: The effectiveness of the proposed method was assessed on two publicly accessible datasets, namely the Montgomery and Shenzhen datasets. The Montgomery dataset comprises 138 X-ray images, while the Shenzhen dataset has 662 X-ray images. The method was further evaluated after combining both datasets. The method performed exceptionally well on all three datasets, achieving high Area Under the Curve (AUC) scores of 0.9978, 0.9836, and 0.9914, respectively, using a 10-fold cross-validation technique. CONCLUSION: The experiments performed in this study prove the effectiveness of features extracted using EfficientnetB0 and Densenet201 in combination with PatternNet classifier in the diagnosis of tuberculosis from X-ray images.

As properties of mono- to few layers of exfoliated van der Waals heterostructures are heavily dependent on their thicknesses, accurate thickness measurement becomes imperative in their study. Commonly used atomic force microscopy and Raman spectroscopy techniques may be invasive and produce inconclusive results. Alternatively, spectroscopic ellipsometry is limited by tens-of-microns lateral resolution and/or low data acquisition rates, inhibiting its utilization for micro-scale exfoliated flakes. In this work, we demonstrate a Fourier imaging spectroscopic micro-ellipsometer with sub-5 microns lateral resolution along with fast data acquisition rate and present angstrom-level accurate and consistent thickness mapping on mono-, bi- and trilayers of graphene, hexagonal boron nitride and transition metal dichalcogenide (MoS2, WS2, MoSe2, WSe2) flakes. We show that the optical microscope integrated ellipsometer can also map minute thickness variations over a micro-scale flake. In addition, our system addresses the pertinent issue of identifying monolayer thick hBN.

Objectives: Organic chemical solvents are generally used during drug material synthesis, excipients, as well as in the drug product formulation. They are not acceptable in the finished product. Hence, the main objective of our work is development and validation of rapid, sensitive, and selective head space gas chromatography (GC-HS) method for the determination of five organic volatile impurities (OVI) (methanol, ethanol, dichloromethane, toluene, and benzene) in Levocloperastine Fendizoate active pharmaceutical ingredient (API) and commercial syrups. Methods: The method was developed using a thermal gradient elution program associated with a column having dimensions are ZB-624, 30 m × 0.53 mm × 3.0 μm with a flow rate of 3.0 mL/min and Nitrogen (N2) as a carrier gas. A flame ionization detector was used as a detector, and its temperature is at 250°C whereas the injector temperature is at 225°C. The total run time is 25.0 min. Results: The newly developed GC-HS method was validated by its specificity and selectivity system precision, and method precision, limit of detection and limit of quantification, linearity, accuracy, robustness, ruggedness, and solution stability as per International Council for Harmonization (ICH). Quantization limits for five impurities were 210 ppm for methanol, 350 ppm for ethanol, 42 ppm for dichloromethane, 62 ppm for toluene, and 0.4 ppm for benzene. Correlation coefficient values of linearity were higher than 0.995 for five OVI. The mean recoveries of five impurities were between 90% and 110%. Conclusion: We found good and accepted results as per ICH guidelines for all validated parameters for five OVI. Thus, the developed GC-HS method was suitable for the separation and quantification of five OVI in Levocloperastine Fendizoate API and commercial syrups at present.

In the last few years, many works have tried to explain the predictions of deep learning models. Few methods, however, have been proposed to verify the accuracy or faithfulness of these explanations. Recently, influence functions, which is a method that approximates the effect that leave-one-out training has on the loss function, has been shown to be fragile. The proposed reason for their fragility remains unclear. Although previous work suggests the use of regularization to increase robustness, this does not hold in all cases. In this work, we seek to investigate the experiments performed in the prior work in an effort to understand the underlying mechanisms of influence function fragility. First, we verify influence functions using procedures from the literature under conditions where the convexity assumptions of influence functions are met. Then, we relax these assumptions and study the effects of non-convexity by using deeper models and more complex datasets. Here, we analyze the key metrics and procedures that are used to validate influence functions. Our results indicate that the validation procedures may cause the observed fragility., 11 pages, 5 figures, published in Neural Networks

"An overview of sandwich structures in aviation applications is provided in this article. It emphasizes the complexity of designing these structures and addresses the main issues that designers face while working with them. Beginning with early instances from the 1930s and focusing on their significant development during World War II, the article examines the evolution of sandwich structures. It explores their wide range of uses in both civil and military spheres. The article also investigates the impact of polymer materials and sheet technology on the mechanical characteristics of composite sandwich constructions. The essay covers three different types of sandwich structures that were created using manual lay-up, press technique, and autoclave application manufacturing processes. These sandwich specimens underwent impact load tests to determine their failure properties. The structural analysis focused on sandwich panels produced in a similar manner, with an adhesive layer between the cores. The goal of the study was to generate research findings about the effects of stress during sandwich panel fabrication on several mechanical properties of structured sandwich composites, including flexural strength, impact strength, and compressive strength.

Abstract: The molecularly imprinted polymers (MIPs) technology, which has been around since the 1970s, has grown in popularity in recent decades. MIPs have shown to be a useful approach for determining target molecules in complicated matrices containing other structurally similar and related chemicals. Despite MIPs have intrinsic polymer features such as stability, robustness, and low-cost production, traditional MIPs have a number of drawbacks. Surface molecular imprinting appears to be an alternative approach that can address some of the drawbacks of traditional MIP by anchoring shells to the surface of matrix carriers such as nanoparticles. The incorporation of nanoparticles into the polymeric structure of MIPs can improve their properties or provide novel capabilities. Magnetic nanoparticles have been widely explored for their separation and extraction capability. Magnetic components in MIP can help develop a regulated rebinding process, allowing magnetic separation to substitute centrifugation and filtration stages in a simple and cost-effective strategy. Polymers are created directly on the surface of a magnetic substrate to create a unique material termed magnetic molecularly imprinted polymer (MMIP). These materials have been widely used to extract molecules from complex matrices in a variety of applications, especially in environmental, food, and biological studies. This paper seeks to summarize and discuss the nanoparticle synthesis and magnetic nanoparticle combination in the MIP preparation. The novel applications of MMIP in environmental, food, and biological analysis are also discussed in this paper.

Neurofibromatosis (NF) is an inherited neuroectodermal abnormality that primarily affects the growth of neural tissues, and Riccardi classified it into eight types. Segmental neurofibromatosis, which is a rare form of neurofibromatosis, is classified as type 5. We report a case for very unusual presentation of segmental NF with unilateral lisch nodules and uncommon sites involving the scalp. Moreover, we could find only one case report of segmental NF with lisch nodules in the literature and could not find any case report involving the scalp.

A Decision Support System (DSS) is a computerized system that helps users make decisions. In the field of air transport, RAL has developed DSSs to support decision making in various settings, including surface transportation and national security. The purpose of this chapter is to explore the maintenance hypothesis of conditional status checking and propose supporting concepts, such as enhanced care and proactive maintenance. These concepts are further enhanced by robust validation and strategies to improve the effectiveness of care in an extraordinary way. Therefore, a decision support system framework is necessary to build today's flying maintenance framework. Maintenance Decision Support Systems (MDSS) offer a valuable tool for aeronautical support, enhancing maintenance efficiency and cost control. However, further research is required to delve into the associated topics of flying MDSS. Due to the diverse configurations and intricate structures of modern aircraft, a significant number of aircraft parameters need to be evaluated. To facilitate further research, it is essential to establish systematic procedures for compiling a valuable database and define research criteria to assess the sufficiency of existing information. Considering the cost issues associated with continuous flight position information, determining the criteria for data download should guide further research.

Background: The Affordable Care Act (ACA) was intended, in part, to reduce the uninsured population. It underwent full implementation in 2014 with optional state Medicaid expansion and health insurance marketplaces. Prior to the ACA, studies show that insurance status affects cancer care, including prevention, diagnosis, stage at diagnosis, and management. ACA impact on malignant melanoma is unknown. In this study, the primary objective is to examine the impact of the ACA on insurance rates among patients diagnosed with malignant melanoma. Survival by insurance type was also assessed. Methods: A retrospective analysis of the Surveillance, Epidemiology and End Results (SEER) cancer registry was performed for malignant melanoma between 2007 (first year of insurance da-ta in SEER) and 2015. Standardized mean differences were used for 2007-2013 and 2014-2015 (after full ACA implementation) for the primary objective. Sub-analysis was performed for Med-icaid expansion and non-expansion states. The impact of insurance type (uninsured, Medicaid, non-Medicaid) on all-cause and cause-specific mortality was assessed via adjusted cox regression models. Results: Nationally, the ACA decreased percentage of uninsured patients (-1.12% to -2.26%, P

For all q ≥ 2 q\ge 2 and for all invertible residue classes a a modulo q q , there exists a natural number that is congruent to a a modulo q q and that is the product of exactly three primes, all of which are below ( 10 15 q ) 5 / 2 (10^{15}q)^{5/2} .

Spatial mode-count scalability in optical fibers is of paramount importance for addressing the upcoming information-capacity crunch, reducing energy consumption per bit, and for enabling advanced quantum computing networks, but this scalability is severely limited by perturbative mode mixing. We show an alternative means of light guidance, in which light’s orbital angular momentum creates a centrifugal barrier for itself, thereby enabling low-loss transmission of light in a conventionally forbidden regime wherein the mode mixing can be naturally curtailed. This enables kilometer-length-scale transmission of a record ~50 low-loss modes with cross-talk as low as −45 decibels/kilometer and mode areas of ~800 square micrometers over a 130-nanometer telecommunications spectral window. This distinctive light-guidance regime promises to substantially increase the information content per photon for quantum or classical networks.

The article engages in a critical reading of the political pattern of Sino-Sri Lankan bilateral engagement. China offers an alternate global order for Sri Lanka by underscoring political discourses like “harmonious world” and “building a community with a shared destiny or future for mankind.” Through these discourses, China attempts to present a “fair and equitable” international system to small states such as Sri Lanka to mobilize them against the universalization of the liberal order. This is part of China's goal to challenge the universalization of liberal values to indicate the Chinese economic and political model as aspirational for developing countries. However, it culminates as the “hegemony of harmony,” as China dictates the terms to protect its national interests, dissimulating cultural relativism and exceptionalism as the foundation of the Chinese-led global order. This article employs historical and descriptive analysis to explain the political nature of Sino-Sri Lankan engagement, elucidating China's specific strategies to harmonize Sri Lanka.

Salem dolerites were collected across the dyke from various parts of the studied area for identifying the differentiation process of magma in the conduits from the compositional profile. The thick dolerites show NNW-SSE, NE-SW, and NW-SE trends. The studied dyke shows systematic composition increasing and decreasing in the chilled margin and centre of the dyke as the texture and concentration of plagioclase and pyroxene increase. Chilled margins show microcrystalline to intersertal, and the centre of the dyke show sub ophitic textures. The compatible oxide MgO, element Ni and the Mg number (100Mg/(Mg+FeT)) increased and the incompatible oxides TiO2, P2O5, and elements Zr decreased from the chilled margin to the centre of the dyke in the compositional profile show reverse fractionation trends (opposite to fractional crystallization) in the studied dykes except for Seeliyampatti dyke. The Seeliyampatti dolerites show opposite compositional variations indicating a normal fractionation trend from the other dykes of the study area. The reverse fractional trends in dykes resulting in the progressive increase of cumulate minerals growth against the dyke wall called the «cumulate process», however, the normal fractional trend in Seeliyampatti resulting in the progressive increase of more evolved magma successively removes the early chilled margin and fills the thick dyke with less compatible and more incompatible components toward the centre of the dyke. Although the normal trend in thick dyke considered the exceptional liquid process of magma differentiation that was formed more like fractional crystallization. Factor analysis also supports the differentiation process of magma. The first factor accounts total variance of 57.68% showing the positively loaded incompatible element and negatively loaded compatible elements.

Mitochondria are critical organelles responsible for the maintenance of cellular energy homeostasis. Thus, their dysfunction can have severe consequences in cells responsible for energy-intensive metabolic function, such as hepatocytes. Extensive research over the last decades have identified compromised mitochondrial function as a central feature in the pathophysiology of liver injury induced by an acetaminophen (APAP) overdose, the most common cause of acute liver failure in the United States. While hepatocyte mitochondrial oxidative and nitrosative stress coupled with induction of the mitochondrial permeability transition are well recognized after an APAP overdose, recent studies have revealed additional details about the organelle’s role in APAP pathophysiology. This concise review highlights these new advances, which establish the central role of the mitochondria in APAP pathophysiology, and places them in the context of earlier information in the literature. Adaptive alterations in mitochondrial morphology as well as the role of cellular iron in mitochondrial dysfunction and the organelle’s importance in liver recovery after APAP-induced injury will be discussed.