The Internet of Things (IoT) has been implemented by multiple manufacturing companies into their production chain as this technology is the main source of digitalization in a production plant. It ...improves the data assembling, productivity of the operation, communication efficiency, and overall manufacturing performance. IoT is also serves to be a good means for improved and efficient warehouse automation. It makes the delivery of products more efficient by calculating the least routes and also reduces the time that is consumed during the management of inventory. The basic objective of Industry 4.0 is to lessen the participation of human operators and to emphasize the automation systems. However, this objective has changed in Industry 5.0, which aims to achieve the maximum benefits through the human–machine interaction by maintaining a balance. Industry 5.0 aims to strengthen the interaction between ever-increasing powerful machinery and the productive abilities of human beings. This paper introduces a detailed overview of IoT in enabling digital transformations and Industry 4.0. The authors have discussed the application of IoT in different industrial sectors, and how the concept of IIoT has evolved. In addition to this, the present paper highlights several research studies that enable the authors to elicit the major challenges, implementation analysis, and future scope of IIoT.
Several humans’ diseases such as; cancer, heart disease, diabetes retain an etiology of epigenetic, and a new therapeutic option termed as “epigenetic therapy” can offer a potential way to treat ...these diseases. A numbers of epigenetic agents such as; inhibitors of DNA methyltransferase (DNMT) and histone deacetylases (HDACs) have grew an intensive investigation, and many of these agents are currently being tested in a clinical trial, while some of them have been approved for the use by the authorities. Since miRNAs can act as tumor suppressors or oncogenes, the miRNA mimics and molecules targeted at miRNAs (antimiRs) have been designed to treat some of the diseases. Much naturally occurring nutrition were discovered to alter the epigenetic states of cells. The nutrition, including polyphenol, flavonoid compounds, and cruciferous vegetables possess multiple beneficial effects, and some can simultaneously change the DNA methylation, histone modifications and expression of microRNA (miRNA). This review mainly summarizes the information of epigenetic agents of DNMTs and HDACs inhibitors, miRNA mimics and antimiRs, as well as the natural nutrition. In addition, some future perspectives related to the epigenetic therapy are also included.
•“Epigenetic therapy” for several humans' diseases targeting DNMTs, HDACs and miRNAs has been proposed.•Many DNMTs and HDACs inhibitors, miRNA mimics and antimiRs are tested in clinical trials.•Polyphenol, flavonoid and organosulfur compounds and cruciferous vegetables can modulate epigenetic states.•Combined effectiveness of different epigenetic nutrition compounds may achieve a better effect than used alone.
Fusarium mycotoxins are the most economically important fungal toxins. Fumonisins, zearalenone and trichothecenes (T-2 toxin, HT-2 toxin, deoxynivalenol, nivalenol etc) are the major representatives ...and most studied of Fusarium mycotoxins. The Fusarium mycotoxins contaminate cereal grains, animal feeds and human food products, and cause huge economic losses and pose a threat to animal and human health globally. Depending on the type, the toxicity of Fusarium mycotoxins and the mechanisms have been well investigated. Epigenetic modifications (DNA methylation, histone modifications and regulation of non-coding RNA) have been implicated in various human diseases and the toxicities in animals caused by Fusarium mycotoxins, including carcinogenesis, genotoxicity and reproductive disorders. On the basis of recently documented data, this review discussed the relationship between the epigenetic modifications and Fusarium mycotoxins-induced toxicities.
•Fusarium mycotoxins are the most economically important fungal toxins.•Epigenetic modifications has become an evolving trend in the field of toxicology of mycotoxins.•Epigenetic mechanisms are involved in the toxicities of Fusarium mycotoxins such as reproductive disorders.•The epigenetic regulating network of Fusarium mycotoxins induced toxicity is proposed.
Discussion of the hematologic complications of vaccination for severe acute respiratory syndrome coronavirus-2 (COVID-19) has primarily focused on the development of vaccine-associated immune ...thrombosis with thrombocytopenia (VITT). Other hematologic complications are uncommon. We report the case of a patient who developed immunoglobulin G (IgG)-mediated autoimmune hemolytic anemia (AIHA) after the Moderna COVID-19 messenger ribonucleic acid (mRNA) vaccine.
Immune checkpoint inhibitors have revolutionized the treatment paradigm of several cancers. However, not all patients respond to treatment. Tumor cells reprogram metabolic pathways to facilitate ...growth and proliferation. This shift in metabolic pathways creates fierce competition with immune cells for nutrients in the tumor microenvironment and generates by-products harmful for immune cell differentiation and growth. In this review, we discuss these metabolic alterations and the current therapeutic strategies to mitigate these alterations to metabolic pathways that can be used in combination with checkpoint blockade to offer a new path forward in cancer management.
Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder, characterized by impairments in social communication and restricted, repetitive behaviors. Neuroimaging studies have ...shown complex patterns and functional connectivity (FC) in ASD, with no clear consensus on brain-behavior relationships or shared patterns of FC with typically developing controls. Here, we used a dimensional approach to characterize two distinct clusters of FC patterns across both ASD participants and controls using
-means clustering. Using multivariate statistical analyses, a categorical approach was taken to characterize differences in FC between subtypes and between diagnostic groups. One subtype was defined by increased FC within resting-state networks and decreased FC across networks compared with the other subtype. A separate FC pattern distinguished ASD from controls, particularly within default mode, cingulo-opercular, sensorimotor, and occipital networks. There was no significant interaction between subtypes and diagnostic groups. Finally, a dimensional analysis of FC patterns with behavioral measures of IQ, social responsiveness, and ASD severity showed unique brain-behavior relations in each subtype and a continuum of brain-behavior relations from ASD to controls within one subtype. These results demonstrate that distinct clusters of FC patterns exist across ASD and controls, and that FC subtypes can reveal unique information about brain-behavior relationships.
Autism spectrum disorder (ASD) is a neurodevelopmental disorder, with high variation in the types of severity of impairments in social communication and restricted, repetitive behaviors. Neuroimaging studies have shown complex patterns of communication between brain regions, or functional connectivity (FC), in ASD. Here, we defined two distinct FC patterns and relationships between FC and behavior in a group of participants consisting of individuals with and without ASD. One subtype was defined by increased FC within distinct networks of brain regions and decreased FC between networks compared with the other subtype. A separate FC pattern distinguished ASD from controls. The interaction between subtypes and diagnostic groups was not significant. Dimensional analyses of FC patterns with behavioral measures revealed unique information about brain-behavior relations in each subtype.
Human aging is characterized by reductions in the ability to remember associations between items, despite intact memory for single items. Older adults also show less selectivity in task-related brain ...activity, such that patterns of activation become less distinct across multiple experimental tasks. This reduced selectivity or dedifferentiation has been found for episodic memory, which is often reduced in older adults, but not for semantic memory, which is maintained with age. We used fMRI to investigate whether there is a specific reduction in selectivity of brain activity during associative encoding in older adults, but not during item encoding, and whether this reduction predicts associative memory performance. Healthy young and older adults were scanned while performing an incidental encoding task for pictures of objects and houses under item or associative instructions. An old/new recognition test was administered outside the scanner. We used agnostic canonical variates analysis and split-half resampling to detect whole-brain patterns of activation that predicted item versus associative encoding for stimuli that were later correctly recognized. Older adults had poorer memory for associations than did younger adults, whereas item memory was comparable across groups. Associative encoding trials, but not item encoding trials, were predicted less successfully in older compared with young adults, indicating less distinct patterns of associative-related activity in the older group. Importantly, higher probability of predicting associative encoding trials was related to better associative memory after accounting for age and performance on a battery of neuropsychological tests. These results provide evidence that neural distinctiveness at encoding supports associative memory and that a specific reduction of selectivity in neural recruitment underlies age differences in associative memory.
This review article comprehensively delves into the rapidly evolving field of domain adaptation in computer and robotic vision. It offers a detailed technical analysis of the opportunities and ...challenges associated with this topic. Domain adaptation methods play a pivotal role in facilitating seamless knowledge transfer and enhancing the generalization capabilities of computer and robotic vision systems. Our methodology involves systematic data collection and preparation, followed by the application of diverse assessment metrics to evaluate the efficacy of domain adaptation strategies. This study assesses the effectiveness and versatility of conventional, deep learning-based, and hybrid domain adaptation techniques within the domains of computer and robotic vision. Through a cross-domain analysis, we scrutinize the performance of these approaches in different contexts, shedding light on their strengths and limitations. The findings gleaned from our evaluation of specific domains and models offer valuable insights for practical applications while reinforcing the validity of the proposed methodologies.