Nuclear receptor corepressors non-canonically drive glucocorticoid receptor-dependent activation of hepatic gluconeogenesis.

Nuclear receptor corepressors (NCoRs) function in multiprotein complexes containing histone deacetylase 3 (HDAC3) to alter transcriptional output primarily through repressive chromatin remodelling at target loci1-5. In the liver, loss of HDAC3 causes a marked hepatosteatosis largely because of de-repression of genes involved in lipid metabolism6,7; however, the individual roles and contribution of other complex members to hepatic and systemic metabolic regulation are unclear. Here we show that adult loss of both NCoR1 and NCoR2 (double knockout (KO)) in hepatocytes phenocopied the hepatomegalic fatty liver phenotype of HDAC3 KO. In addition, double KO livers exhibited a dramatic reduction in glycogen storage and gluconeogenic gene expression that was not observed with hepatic KO of individual NCoRs or HDAC3, resulting in profound fasting hypoglycaemia. This surprising HDAC3-independent activation function of NCoR1 and NCoR2 is due to an unexpected loss of chromatin accessibility on deletion of NCoRs that prevented glucocorticoid receptor binding and stimulatory effect on gluconeogenic genes. These studies reveal an unanticipated, non-canonical activation function of NCoRs that is required for metabolic health.

Multi-generational labour markets: Data-driven discovery of multi-perspective system parameters using machine learning.

The impact of aggressive capitalist approaches on social, economic and planet sustainability is significant. Economic issues such as inflation, energy costs, taxes and interest rates persist and are further exacerbated by global events such as wars, pandemics and environmental disasters. A sustained history of financial crises exposes weaknesses in modern economies. The Great Attrition, with many quitting jobs, adds to concerns. The diversity of the workforce poses new challenges. Transformative approaches are essential to safeguard societies, economies and the planet. In this work, we use big data and machine learning methods to discover multi-perspective parameters for multi-generational labour markets. The parameters for the academic perspective are discovered using 35,000 article abstracts from the Web of Science for the period 1958-2022 and for the professionals' perspective using 57,000 LinkedIn posts from 2022. We discover a total of 28 parameters and categorized them into five macro-parameters, Learning & Skills, Employment Sectors, Consumer Industries, Learning & Employment Issues and Generations-specific Issues. A complete machine learning software tool is developed for data-driven parameter discovery. A variety of quantitative and visualization methods are applied and multiple taxonomies are extracted to explore multi-generational labour markets. A knowledge structure and literature review of multi-generational labour markets using over 100 research articles is provided. It is expected that this work will enhance the theory and practice of artificial intelligence-based methods for knowledge discovery and system parameter discovery to develop autonomous capabilities and systems and promote novel approaches to labour economics and markets, leading to the development of sustainable societies and economies.

CRISPR-based epigenome editing: mechanisms and applications.

Epigenomic anomalies contribute significantly to the development of numerous human disorders. The development of epigenetic research tools is essential for understanding how epigenetic marks contribute to gene expression. A gene-editing technique known as CRISPR (clustered regularly interspaced short palindromic repeats) typically targets a particular DNA sequence using a guide RNA (gRNA). CRISPR/Cas9 technology has been remodeled for epigenome editing by generating a 'dead' Cas9 protein (dCas9) that lacks nuclease activity and juxtaposing it with an epigenetic effector domain. Based on fusion partners of dCas9, a specific epigenetic state can be achieved. CRISPR-based epigenome editing has widespread application in drug screening, cancer treatment and regenerative medicine. This paper discusses the tools developed for CRISPR-based epigenome editing and their applications.

Production, purification, and characterization of p-diphenol oxidase (PDO) enzyme from lignolytic fungal isolate Schizophyllum commune MF-O5.

Fungi are producers of lignolytic extracellular enzymes which are used in industries like textile, detergents, biorefineries, and paper pulping. This study assessed for the production, purification, and characterization of novel p-diphenol oxidase (PDO; laccase) enzyme from lignolytic white-rot fungal isolate. Fungi samples collected from different areas of Pakistan were initially screened using guaiacol plate method. The maximum PDO producing fungal isolate was identified on the basis of ITS (internal transcribed spacer sequence of DNA of ribosomal RNA) sequencing. To get optimum enzyme yield, various growth and fermentation conditions were optimized. Later PDO was purified using ammonium sulfate precipitation, size exclusion, and anion exchange chromatography and characterized. It was observed that the maximum PDO producing fungal isolate was Schizophyllum commune (MF-O5). Characterization results showed that the purified PDO was a monomeric protein with a molecular mass of 68 kDa and showed stability at lower temperature (30 °C) for 1 h. The Km and Vmax values of the purified PDO recorded were 2.48 mM and 6.20 U/min. Thermal stability results showed that at 30 °C PDO had 119.17 kJ/K/mol Ea value and 33.64 min half-life. The PDO activity was stimulated by Cu2+ ion at 1.0 mM showing enhanced activity up to 111.04%. Strong inhibition effect was noted for Fe2+ ions at 1 mM showing 12.04% activity. The enzyme showed stability against 10 mM concentration oxidizing reducing agents like DMSO, EDTA, H2O2, NaOCl, and urea and retained more than 75% of relative activity. The characterization of purified PDO enzyme confirmed its tolerance against salt, metal ions, organic solvents, and surfactants indicating its ability to be used in the versatile commercial applications.

Confirming High-Valent Iron as Highly Active Species of Water Oxidation on the Fe, V-Coupled Bimetallic Electrocatalyst: In Situ Analysis of X-ray Absorption and Mössbauer Spectroscopy.

Iron (Fe)-based bimetallic oxides/hydroxides have been widely investigated for promising alkaline electrochemical oxygen evolution reactions (OERs), but it still remains argumentative whether Fe3+ or Fe4+ intermediates are highly active for efficient OER. Here, we rationally designed and prepared one Fe, V-based bimetallic composite nanosheet by employing the OER-inert V element as a promoter to completely avoid the argument of real active metals and using our recently developed one-dimensional conductive nickel phosphide (NP) as a support. The as-obtained hierarchical nanocomposite (denoted as FeVOx/NP) was evaluated as a model catalyst to gain insight into the iron-based species as highly active OER sites by performing in situ X-ray absorption spectroscopy and 57Fe Mössbauer spectroscopy measurements. It was found that the high-valent Fe4+ species can only be detected during the OER process of the FeVOx/NP nanocomposite instead of the iron counterpart itself. Together with the fact that the OER activities of both the vanadium and iron counterparts are by far worse than that of the FeVOx/NP composite, we can confirm that the high-valent Fe4+ formed are the highly active species for efficient OER. As demonstrated by density functional theory simulations, the composite of Fe and V metals is proposed to cause a decreased Gibbs free energy as well as theoretical overpotential of water oxidation with respect to its counterparts, as is responsible for its excellent OER performance with extremely low OER overpotential (290 mV at 500 mA cm-2) and extraordinary stability (1000 h at 100 mA cm-2).

Absence of GSTT1 and polymorphisms in GSTP1 and TP53 are associated with the incidence of acne vulgaris.

BACKGROUNDS: Acne vulgaris is a chronic inflammatory skin disease of the pilosebaceous unit affecting most teenagers and numerous adults throughout the world. The present study was designed to assess the association of the presence or absence of GSTM1, GSTT1, and single nucleotide polymorphisms rs1695 in GSTP1 and rs1042522 in TP53 gene with acne vulgaris. METHODS: The cross-sectional case-control study was conducted at the Institute of Zoology from May 2020 to March 2021 and included acne vulgaris patients (N = 100) and controls (N = 100) enrolled in Dera Ghazi Khan district, Pakistan. Multiplex and tetra-primer amplification refractory mutation system-polymerase chain reactions were applied to investigate the genotype in analyzed genes. The association of rs1695 and rs1042522 with acne vulgaris was studied either individually or in various combinations with GATM1 and T1. RESULTS: A significant association of absence of GSTT1 and mutant genotype at rs1695 (GG) and at rs1042522 (CC) in GSTP1 and TP53, respectively, was found to be associated with acne vulgaris in enrolled subjects. Subjects aged 10-25 years and smokers were more susceptible to acne vulgaris. CONCLUSION: Our results suggest that genotypes of glutathione S-transferases (GSTs) and TP53 are involved in protection against oxidative stress and may influence disease progression in acne vulgaris.

Discriminatory practices and poor job performance: A study of person-related hostility among nursing staff.

This study highlights the organisational-level factors that become the reason for propagating hostile behaviours among female nurses. Freire's theory of oppression has been used as an underpinning theory for developing the conceptual framework. This study empirically verifies the conceptual framework of the study that gender discrimination and lack of administrative support are the antecedents of person-related hostility, which is the reason for poor job performance in the healthcare sector. We applied a quantitative research approach, using questionnaires to collect data. Total of 707 survey forms were collected from female nurses working in public sector hospitals in four main cities of Pakistan. The software SPSS 20 and SmartPLS 3 were used for the final data analysis. All hypotheses regarding the direct and indirect relationship of variables were accepted. Gender discrimination and lack of administrative support were positively associated with person-related hostility. Moreover, person-related hostility also mediated the relationship between independent variables (gender discrimination, lack of administrative support) and dependent variable (poor job performance). Future research is directed to study person-related hostility among nursing staff of semi-urban areas and small towns with low literacy rates, considering other dependent variables like burnout, mental well-being, and mental health. HR strategies and policies for fair performance evaluation and timely promotions of nursing professionals are proposed in the study for building an overall healthy environment.

Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses.

Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment; however, more important is to remove the root causes of mental illnesses because doing so can help prevent mental health problems from occurring or recurring. This requires a holistic approach to understanding mental health issues that are missing from the existing research. Mental health should be understood in the context of social and environmental factors. More research and awareness are needed, as well as interventions to address root causes. The effectiveness and risks of medications should also be studied. This paper proposes a big data and machine learning-based approach for the automatic discovery of parameters related to mental health from Twitter data. The parameters are discovered from three different perspectives: Drugs and Treatments, Causes and Effects, and Drug Abuse. We used Twitter to gather 1,048,575 tweets in Arabic about psychological health in Saudi Arabia. We built a big data machine learning software tool for this work. A total of 52 parameters were discovered for all three perspectives. We defined six macro-parameters (Diseases and Disorders, Individual Factors, Social and Economic Factors, Treatment Options, Treatment Limitations, and Drug Abuse) to aggregate related parameters. We provide a comprehensive account of mental health, causes, medicines and treatments, mental health and drug effects, and drug abuse, as seen on Twitter, discussed by the public and health professionals. Moreover, we identify their associations with different drugs. The work will open new directions for a social media-based identification of drug use and abuse for mental health, as well as other micro and macro factors related to mental health. The methodology can be extended to other diseases and provides a potential for discovering evidence for forensics toxicology from social and digital media.

Rational design of heterogenized molecular phthalocyanine hybrid single-atom electrocatalyst towards two-electron oxygen reduction.

Single-atom catalysts supported on solid substrates have inspired extensive interest, but the rational design of high-efficiency single-atom catalysts is still plagued by ambiguous structure determination of active sites and its local support effect. Here, we report hybrid single-atom catalysts by an axial coordination linkage of molecular cobalt phthalocyanine with carbon nanotubes for selective oxygen reduction reaction by screening from a series of metal phthalocyanines via preferential density-functional theory calculations. Different from conventional heterogeneous single-atom catalysts, the hybrid single-atom catalysts are proven to facilitate rational screening of target catalysts as well as understanding of its underlying oxygen reduction reaction mechanism due to its well-defined active site structure and clear coordination linkage in the hybrid single-atom catalysts. Consequently, the optimized Co hybrid single-atom catalysts exhibit improved 2e- oxygen reduction reaction performance compared to the corresponding homogeneous molecular catalyst in terms of activity and selectivity. When prepared as an air cathode in an air-breathing flow cell device, the optimized hybrid catalysts enable the oxygen reduction reaction at 300 mA cm-2 exhibiting a stable Faradaic efficiency exceeding 90% for 25 h.

Crosswise Stream of Cu-H2O Nanofluid with Micro Rotation Effects: Heat Transfer Analysis.

The present study focuses on a crosswise stream of liquid-holding nano-sized particles over an elongating (stretching) surface. Tiny particles of copper are added into base liquid (water). The influence of the micro rotation phenomenon is also considered. By means of appropriate transformations non-linear coupled ordinary differential equations are attained that govern the flow problem. The Runge-Kutta-Fehlberg scheme, together with the shooting method, is engaged to acquire results numerically. Micropolar coupling parameter, microelements concentration and nanoparticles volume fraction effects are examined over the profiles of velocity, temperature and micro-rotation. Moreover, heat flux and shear stress are computed against pertinent parameters and presented through bar graphs. Outcomes revealed that material constant has increasing effects on normal components of flow velocity; however, it decreasingly influences the tangential velocity, micro-rotation components and temperature profile. Temperature profile appeared to be higher for weak concentration of microelements. It is further noticed that normal velocity profile is higher in magnitude for the case of strong concentration (n = 0) of microelements, whereas tangential velocity profile is higher near the surface for the case of weak concentration (n = 0.5) of microelements. An increase of 3.74% in heat flux is observed when the volume fraction of nanoparticles is increased from 1 to 5%.

The Nodewalk assay to quantitate chromatin fiber interactomes in very small cell populations.

The chromosome conformation capture method and its derivatives, such as circularized chromosome conformation capture, carbon copy chromosome conformation capture, high-throughput chromosome conformation capture and capture high-throughput chromosome conformation capture, have pioneered our understanding of the principles of chromosome folding in the nucleus. These technical advances, however, cannot precisely quantitate interaction frequency in very small input samples. Here we describe a protocol for the Nodewalk assay, which is based on converting chromosome conformation capture DNA samples to RNA and subsequently to cDNA using strategically placed primers. This pipeline enables the quantitative analyses of chromatin fiber interactions without compromising its sensitivity down to <300 cells, making it suitable for MiSeq analyses of higher-order chromatin structures in biopsies, circulating tumor cells and transitional cell states, for example. Importantly, the quality of the Nodewalk sample can be assessed before sequencing to avoid unnecessary costs. Moreover, it enables analyses from hundreds of different restriction enzyme fragment viewpoints within the same initial small input sample to uncover complex, genome-wide networks. Following optimization of the different steps, the entire protocol can be completed within 2 weeks.

2D-2D heterostructure g-C3N4-based materials for photocatalytic H2 evolution: Progress and perspectives.

Photocatalytic hydrogen generation from direct water splitting is recognized as a progressive and renewable energy producer. The secret to understanding this phenomenon is discovering an efficient photocatalyst that preferably uses sunlight energy. Two-dimensional (2D) graphitic carbon nitride (g-C3N4)-based materials are promising for photocatalytic water splitting due to special characteristics such as appropriate band gap, visible light active, ultra-high specific surface area, and abundantly exposed active sites. However, the inadequate photocatalytic activity of pure 2D layered g-C3N4-based materials is a massive challenge due to the quick recombination between photogenerated holes and electrons. Creating 2D heterogeneous photocatalysts is a cost-effective strategy for clean and renewable hydrogen production on a larger scale. The 2D g-C3N4-based heterostructure with the combined merits of each 2D component, which facilitate the rapid charge separation through the heterojunction effect on photocatalyst, has been evidenced to be very effective in enhancing the photocatalytic performance. To further improve the photocatalytic efficiency, the development of novel 2D g-C3N4-based heterostructure photocatalysts is critical. This mini-review covers the fundamental concepts, recent advancements, and applications in photocatalytic hydrogen production. Furthermore, the challenges and perspectives on 2D g-C3N4-based heterostructure photocatalysts demonstrate the future direction toward sustainability.

Developing Smartness in Emerging Environments and Applications with a Focus on the Internet of Things.

The smartness that underpins smart cities and societies is defined by our ability to engage with our environments, analyze them, and make decisions, all in a timely manner [...].

LidSonic V2.0: A LiDAR and Deep-Learning-Based Green Assistive Edge Device to Enhance Mobility for the Visually Impaired.

Over a billion people around the world are disabled, among whom 253 million are visually impaired or blind, and this number is greatly increasing due to ageing, chronic diseases, and poor environments and health. Despite many proposals, the current devices and systems lack maturity and do not completely fulfill user requirements and satisfaction. Increased research activity in this field is required in order to encourage the development, commercialization, and widespread acceptance of low-cost and affordable assistive technologies for visual impairment and other disabilities. This paper proposes a novel approach using a LiDAR with a servo motor and an ultrasonic sensor to collect data and predict objects using deep learning for environment perception and navigation. We adopted this approach using a pair of smart glasses, called LidSonic V2.0, to enable the identification of obstacles for the visually impaired. The LidSonic system consists of an Arduino Uno edge computing device integrated into the smart glasses and a smartphone app that transmits data via Bluetooth. Arduino gathers data, operates the sensors on the smart glasses, detects obstacles using simple data processing, and provides buzzer feedback to visually impaired users. The smartphone application collects data from Arduino, detects and classifies items in the spatial environment, and gives spoken feedback to the user on the detected objects. In comparison to image-processing-based glasses, LidSonic uses far less processing time and energy to classify obstacles using simple LiDAR data, according to several integer measurements. We comprehensively describe the proposed system's hardware and software design, having constructed their prototype implementations and tested them in real-world environments. Using the open platforms, WEKA and TensorFlow, the entire LidSonic system is built with affordable off-the-shelf sensors and a microcontroller board costing less than USD 80. Essentially, we provide designs of an inexpensive, miniature green device that can be built into, or mounted on, any pair of glasses or even a wheelchair to help the visually impaired. Our approach enables faster inference and decision-making using relatively low energy with smaller data sizes, as well as faster communications for edge, fog, and cloud computing.

Reading habits of medical practitioners: Young doctors in Pakistan, a case study.

Objective: This study attempted to investigate the reading preferences and habits among young Pakistani medical doctors. The reading time, preferred source of information, preferred medical journals, and ways of reading medical journals were explored. Methods: A survey approach was used for data collection. The study participants were young medical professionals in Pakistan. An online survey was sent to more than 300 individuals through various physicians and their professional groups/bodies. A total of 155 responded to the questionnaire, and 128 of the questionnaires were considered worthy of data analysis. Results: Among respondents, 40% read printed journals, 49% read online journals, 60% read case reports, and 55% read newspapers for 1-5 h per week. Continuing medical education was the preferred source of information, and the Pakistan Journal of Cardiology & Thoracic Surgery was the preferred medical journal. Reading the abstract and the conclusion was the preferred way of reading journal articles. Conclusion: Young physicians are enthusiastic in participating in research activities and spending time gaining updated information. Physicians read articles methodically. Online sources of information are preferred over printed sources.

Efficiently suppress of ferroptosis using deferoxamine nanoparticles as a new method for retinal ganglion cell protection after traumatic optic neuropathy.

Traumatic optic neuropathy (TON) is the major contributor to optic nerve damage, where the retinal ganglion cells (RGCs) are substantially lost. However, the underlying pathological mechanisms for these conditions remain largely elusive. Present work conducted a study on TON rat model, where the iron-dependent cyclooxygenase-2 (COX-2) overexpression and lipid peroxidation were observed in RGCs, suggesting ferroptosis, an iron-dependent non-apoptotic cell death, is involved in TON-induced death of RGCs. Hence, the newly formulated hyaluronic acid (HA)-based deferoxamine (DFO) nanoparticles (DFO-NPs) were intravitreally administrated in the rat model. It was hypothesized that the effective delivery of DFO, iron chelator, to the RGCs might rescue RGC ferroptosis from TON-induced injury. Also, since DFO is poor in bioavailability and of very short half-life in vivo, its safe and efficient intravitreal delivery is critical. Therefore, DFO-NPs were prepared by chemical grafting DFO onto HA molecules, and then crosslinking them in microemulsion bubbles for nanoparticles formulation. The nanoparticles were highly accumulated around the ganglionic cells and DFO uptake was increased in RGCs, accompanied by the significantly inhibited the overexpression of COX-2 and inactivation of glutathione peroxidase 4 (GPX4). These results indicate that DFO-NPs acted as an effective ferroptosis inhibitor, for the prevention of TON-induced RGC death. The current study provides new insights into the underlying mechanism of TON-induced RGC death, which may help to explore a novel strategy for the treatment of TON.

Implementing High-Reliability Organization Principles at Biological Diagnostic Laboratories: Case Study at National Institute of Health, Islamabad.

Introduction: Healthcare organizations are complex systems where healthcare professionals, patients, biological materials, and equipment constantly interact and provide feedback with highly consequential outcomes. These are the characteristics of a complex adaptive system. Healthcare delivery requires coordination but it necessarily relies on delegation of essential functions. It is thus essential to have an engaged workforce to ensure optimal outcomes for patients. Thus human performance factors play a key role in ensuring both the presence of excellent healthcare provision and the absence of outcomes that must be avoided-"never events." Methods: The commitment of management was a precondition for the implementation of the high-reliability organization (HRO) principles. A team from middle management was engaged and provided with appropriate management tools for identifying, prioritizing, assessing, and applying solutions for the safety concern in their operating systems. Results: This article documents efforts at the National Institute of Health (NIH) to adapt the principles of HROs to diagnostic laboratories and vaccine production facilities at its campus in Islamabad, Pakistan, and seeks to draw some lessons for how this approach can be usefully replicated in such facilities elsewhere. Conclusion: Public health institutes such as NIH deliver vital products and services that are inherently risky to produce, where the consequence of failure can be catastrophic. Adopting the HRO principles is an approach to improving not just safety, but also the overall organizational performance in any setting, including low-resource settings, and can serve as an implementable process for other institutions.

Molecular Epidemiology of Cryptosporidium parvum and Giardia lamblia in Different Water Bodies, Soil, and Vegetables in Pakistan.

There is a dearth of knowledge regarding transmission of Cryptosporidium (C) and Giardia (G) species through water and water-related sources in Pakistan. To this end, we conducted a study to evaluate the prevalence of these parasites in different water bodies, soil, and mixed raw vegetables in Pakistan. Researchers collected 200 samples from each reservoir including municipal water, sewage water, canal water, raw vegetables, soil of public parks, and soil of grazing areas. Researchers amplified the 18S ribosomal RNA gene of parasites using newly designed genus-specific primers through polymerase chain reaction testing. The sequencing analysis revealed that the obtained sequences belonged to C parvum and G lamblia. Phylogenetic clustering and sequence analysis of C parvum showed that the C parvum Pak1 (OM540369) and C parvum Pak2 (OM540370) as well as C parvum Pak3 (OM510450) and C parvum Pak6 (OM510445) were closely similar to each other. In the case of G lamblia, all the sequences appeared in the same clade. The epidemiological data showed lower prevalence of C parvum (11.5%) in all reservoirs, compared with G lamblia (20.5%). Among different reservoirs, prevalence of Cryptosporidium and Giardia was observed in sewage water (C = 13%, G = 26.5%), municipal water (C = 10%, G = 35%), canal water (C = 9.5%, G = 18.5%), raw vegetables (C = 5.5%, G = 8%), soil of public parks (C = 13%, G = 14%), and soil of grazing areas (C = 18.5%, G = 21.5%). Among targeted risk factors, poor hygienic conditions significantly affected the prevalence of parasites in sewage water (C = 20%, G = 41.2%), municipal water (C = 14.7%, G = 48.8.5%), raw vegetables (C = 11.3%, G = 15.1%), and soil of public parks (C = 19.5%, G = 21.9%). Similarly, contamination with sewage waste significantly affected (P < .05) the prevalence of these parasites in municipal water (C = 13.6%, G = 41.1%), canal water (C = 13.3%, G = 25%), raw vegetables (C = 12.1%, G = 15.1%), and soil of public parks (C = 23.3%, G = 15%). Results of this study illustrated a high risk of parasitic zoonosis through water bodies, soil, and vegetables.

Anticancer therapeutic effect of cerium-based nanoparticles: known and unknown molecular mechanisms.

Cerium-based nanoparticles (CeNPs), particularly cerium oxide (CeO2), have been studied extensively for their antioxidant and prooxidant properties. However, their complete redox and enzyme-mimetic mechanisms of therapeutic action at the molecular level remain elusive, constraining their potential for clinical translation. Although the therapeutic effects of both antioxidant and prooxidant mechanisms generally are attributed to Ce3+ ↔ Ce4+ redox switching mediation, some studies have hinted at the involvement of unknown pathways in therapeutic effects. While redox switching is recognised increasingly as playing a key role in ROS-dependent cancer therapy, ROS-independent cytotoxicity mechanisms, such as Ce4+ dissolution and autophagy, also are emerging as being of importance. Although ROS-mediated prooxidant therapies are the most intensively studied, particularly in the context of cancer, the antioxidant activity deriving from the redox switching, particularly during radiation therapy, also plays an important role in the protection of normal cells during radiation therapy, hence reducing adverse effects. Since cancer cell proliferation results in aberrant behaviour of the tumour microenvironment (TME), then CeNP-based therapies are being used to address a multiplicity of known and unknown factors that aim to normalise the TME and thus prevent this aberrant behaviour. Although it is perceived that the pH plays a key role in the therapeutic performance of cerium-based nanoparticles, this is not conclusive because the relative importances of other factors, particularly Ce dissolution, Ce3+/Ce4+ ratio, cellular H2O2 level, and the role of anions, remain poorly understood. Consequently, the present work explores these multiple chemistry-driven mechanisms, which are both ROS-dependent and ROS-independent, in cancer therapy.

Imtidad: A Reference Architecture and a Case Study on Developing Distributed AI Services for Skin Disease Diagnosis over Cloud, Fog and Edge.

Several factors are motivating the development of preventive, personalized, connected, virtual, and ubiquitous healthcare services. These factors include declining public health, increase in chronic diseases, an ageing population, rising healthcare costs, the need to bring intelligence near the user for privacy, security, performance, and costs reasons, as well as COVID-19. Motivated by these drivers, this paper proposes, implements, and evaluates a reference architecture called Imtidad that provides Distributed Artificial Intelligence (AI) as a Service (DAIaaS) over cloud, fog, and edge using a service catalog case study containing 22 AI skin disease diagnosis services. These services belong to four service classes that are distinguished based on software platforms (containerized gRPC, gRPC, Android, and Android Nearby) and are executed on a range of hardware platforms (Google Cloud, HP Pavilion Laptop, NVIDIA Jetson nano, Raspberry Pi Model B, Samsung Galaxy S9, and Samsung Galaxy Note 4) and four network types (Fiber, Cellular, Wi-Fi, and Bluetooth). The AI models for the diagnosis include two standard Deep Neural Networks and two Tiny AI deep models to enable their execution at the edge, trained and tested using 10,015 real-life dermatoscopic images. The services are evaluated using several benchmarks including model service value, response time, energy consumption, and network transfer time. A DL service on a local smartphone provides the best service in terms of both energy and speed, followed by a Raspberry Pi edge device and a laptop in fog. The services are designed to enable different use cases, such as patient diagnosis at home or sending diagnosis requests to travelling medical professionals through a fog device or cloud. This is the pioneering work that provides a reference architecture and such a detailed implementation and treatment of DAIaaS services, and is also expected to have an extensive impact on developing smart distributed service infrastructures for healthcare and other sectors.