How Far Is the Nanocellulose Chip and Its Production in Reach? A Literature Survey.

The slowdown of Moore's Law necessitates an exploration of novel computing methodologies, new materials, and advantages in chip design. Thus, carbon-based materials have promise for more energy-efficient computing systems in the future. Moreover, sustainability emerges as a new concern for the semiconductor industry. The production and recycling processes associated with current chips present huge environmental challenges. Electronic waste is a major problem, and sustainable solutions in computing must be found. In this review, we examine an alternative chip design based on nanocellulose, which also features semiconductor properties and transistors. Our review highlights that nanocellulose (NC) is a versatile material and a high-potential composite, as it can be fabricated to gain suitable electronic and semiconducting properties. NC provides ideal support for ink-printed transistors and electronics, including green paper electronics. Here, we summarise various processing procedures for nanocellulose and describe the structure of exclusively nanocellulose-based transistors. Furthermore, we survey the recent scientific efforts in organic chip design and show how fully automated production of such a full NC chip could be achieved, including a Process Design Kit (PDK), expected variation models, and a standard cell library at the logic-gate level, where multiple transistors are connected to perform basic logic operations-for instance, the NOT-AND (NAND) gate. Taking all these attractive nanocellulose features into account, we envision how chips based on nanocellulose can be fabricated using Electronic Design Automation (EDA) tool chains.

Mild hunger elicits attentional desensitization to visual food cues in healthy, non-obese individuals.

Introduction: Food is a vital human need, and the human visual system is finely tuned to detect and respond to food cues in the environment. The omnipresence of food cues across various settings has been linked to the prevalence of obesity in susceptible populations. However, the influence of the post-prandial state on visual attention to food stimuli remains poorly understood. This study aimed to elucidate how a 12 hour fast affects visual attention to food and non-food stimuli in healthy, non-obese individuals. Methods: Visual attention was assessed by measuring the total duration of visual fixations on stimuli presented on a computer screen, using a screen-based eye tracker (Tobii X2-60). Participants were divided into two groups: those who had fasted for 12 hours and those tested within two hours after consuming breakfast (satiated state). Additionally, performance on the Food Stroop task and electrodermal activity (EDA) responses were measured to evaluate attentional interference and physiological arousal, respectively. Salivary samples were also collected to assess levels of alpha-amylase and cortisol. Results: Fasted participants exhibited a progressive decline in visual attention toward food stimuli compared to satiated individuals, reflecting a satiated state. This effect was independent of the palatability of the depicted food items and was not observed with stimuli representing non-food items. The Food Stroop task revealed no differences between fasting and satiated participants, indicating that the presence of food-related stimuli does not differentially impact attentional interference under varying hunger states. Moreover, no significant variations were observed in EDA responses across participant groups and stimulus types, suggesting that the modulation of visual attention to food cues by hunger is independent of physiological arousal. Interestingly, satiated subjects exhibited higher levels of salivary alpha-amylase, which was inversely related to their subjective hunger ratings. No differences in salivary cortisol levels were found between groups. Discussion: The findings indicate a novel influence of mild hunger on the processing of visual food cues, independent of physiological arousal. The decline in visual attention to food stimuli in fasted individuals suggests that satiety modulates visual processing. The lack of differences in attentional interference and physiological arousal between fasting and satiated states further supports the notion that visual attention to food cues is primarily driven by hunger-related mechanisms rather than stress. Additionally, the inverse relationship between salivary alpha-amylase levels and hunger ratings implies that alpha-amylase may serve as a marker of satiety rather than stress.

The Impact of Physiological and Psychological Fatigue on Work Efficiency: A Case Study of Parcel Sorting Work.

The popularity of online shopping in China has increased significantly, creating new development opportunities for the express delivery industry. However, the rapid expansion of the express industry has also created challenges in the parcel sorting process. The demanding nature of parcel sorting work, which is characterized by intense and prolonged repetitive tasks, makes individuals particularly vulnerable to the effects of fatigue. Fatigue is a complex condition that encompasses both physiological and psychological exhaustion. It often results in reduced energy levels and diminished functionality, significantly impacting an individual's performance at work and their overall well-being. This study aimed to investigate how physiological and psychological fatigue affects sorting efficiency and to identify appropriate rest periods that will allow employees to maintain their performance levels. The research involved fifteen participants who took part in a 60 min continuous sorting experiment and a similar experiment with scheduled breaks. During both trials, we collected data on participants' electromyography (EMG) and electrodermal activity (EDA), as well as subjective fatigue ratings (RPE). Signal features such as the median frequency (MF) of EMG and the skin conductance level (SCL) were analyzed to assess physiological and psychological fatigue, respectively. The results show that physiological fatigue mainly affects sorting efficiency in the first 30 min, while psychological fatigue becomes more influential in the following half-hour period. In addition, subjective fatigue levels during the first 30 min are primarily determined by psychological factors, while beyond that point, both physiological and psychological fatigue contribute to subjective fatigue. Rest periods of 415-460 s, based on EDA recovery times, effectively support sorting efficiency and participants' recovery. This study highlights the complex ways in which fatigue affects parcel sorting performance and provides valuable theoretical and practical insights for establishing labor quotas and optimizing work schedules in the parcel sorting industry.

Machine learning based classification of presence utilizing psychophysiological signals in immersive virtual environments.

In Virtual Reality (VR), a higher level of presence positively influences the experience and engagement of a user. There are several parameters that are responsible for generating different levels of presence in VR, including but not limited to, graphical fidelity, multi-sensory stimuli, and embodiment. However, standard methods of measuring presence, including self-reported questionnaires, are biased. This research focuses on developing a robust model, via machine learning, to detect different levels of presence in VR using multimodal neurological and physiological signals, including electroencephalography and electrodermal activity. An experiment has been undertaken whereby participants (N = 22) were each exposed to three different levels of presence (high, medium, and low) in a random order in VR. Four parameters within each level, including graphics fidelity, audio cues, latency, and embodiment with haptic feedback, were systematically manipulated to differentiate the levels. A number of multi-class classifiers were evaluated within a three-class classification problem, using a One-vs-Rest approach, including Support Vector Machine, k-Nearest Neighbour, Extra Gradient Boosting, Random Forest, Logistic Regression, and Multiple Layer Perceptron. Results demonstrated that the Multiple Layer Perceptron model obtained the highest macro average accuracy of 93 ± 0.03 % . Posthoc analysis revealed that relative band power, which is expressed as the ratio of power in a specific frequency band to the total baseline power, in both the frontal and parietal regions, including beta over theta and alpha ratio, and differential entropy were most significant in detecting different levels of presence.

Estimation of suspected estrogenic transformation products generated during preservative butylparaben chlorination using a simplified effect-based analysis approach.

Estrogenic transformation products (TPs) generated after water chlorination can be considered as an environmental and health concern, since they can retain and even increase the estrogenicity of the parent compound, thus posing possible risks to drinking water safety. Identification of the estrogenic TPs generated from estrogenic precursor during water chlorination is important. Herein, butylparaben (BuP), which was widely used as preservative in food, pharmaceuticals and personal care products (PPCPs), was selected for research. A simplified effect-based analysis (EDA) approach was applied for the identification of estrogenic TPs generated during BuP chlorination. Despite the removal of BuP corresponds to the decrease of estrogenicity in chlorinated samples, an significant increase of estrogenicity was observed (at T = 30 min, presented an estrogenicity equivalent to 17ß-estradiol). Chemical analysis of the estrogenic chlorinated samples that have been previously subjected to biological analysis (in vitro assays), in combination with the principal component analysis (PCA) evaluation, followed by validating the estrogenic potency of most relevant estrogenic TPs through an in silico approach (molecular dynamics simulations), identified that the halogenated TP3 (3,5-Dichloro-butylparaben) increased by 62.5 % and 61.8 % of the estrogenic activity of the parent compound in samples chlorinated with 30 min and 1 h, respectively being classified as a potentially estrogenic activity driver after BuP chlorination. This study provides a scientific basis for the more comprehensive assessment of the environmental and health risk associated with BuP chlorination, highlighting the necessity of identifying the unknown estrogenic TPs generateded from estrogenic precursors chlorination.

Targeting alternative splicing of fibronectin in human renal proximal tubule epithelial cells with antisense oligonucleotides to reduce EDA+ fibronectin production and block an autocrine loop that drives renal fibrosis.

TGFß1 is a powerful regulator of fibrosis; secreted in a latent form, it becomes active after release from the latent complex. During tissue fibrosis, the EDA + isoform of cellular fibronectin is overexpressed. In pulmonary fibrosis it has been proposed that the fibronectin splice variant including an EDA domain (FN EDA+) activates latent TGFß. Our work investigates the potential of blocking the 'splicing in' of EDA with antisense oligonucleotides to inhibit TGFß1-induced EDA + fibronectin and to prevent the cascade of events initiated by TGFß1 in human renal proximal tubule cells (PTEC). Human primary PTEC were treated with TGFß1 for 48 h, medium removed and the cells transfected with RNase H-independent antisense oligonucleotides (ASO) designed to block EDA exon inclusion (ASO5). The efficacy of ASO to block EDA exon inclusion was assessed by EDA + fibronectin RNA and protein expression; the expression of TGFß, αSMA (α smooth muscle actin), MMP2 (matrix metalloproteinse-2), MMP9 (matrix metalloproteinse-9), Collagen I, K Cadherin and connexin 43 was analysed. Targeting antisense oligonucleotides designed to block EDA exon inclusion in fibronectin pre mRNA were effective in reducing the amount of TGFß1 -induced cellular EDA + fibronectin RNA and secreted EDA + fibronectin protein (assessed by western immunoblotting and immunocytochemistry) in human proximal tubule cells in an in vitro cell culture model. The effect was selective for EDA + exon with no effect on EDB + fibronectin RNA and total fibronectin mRNA. Exogenous TGFß1 induced endogenous TGFß, αSMA, MMP2, MMP9 and Col I mRNA. TGFß1 treatment for 48h reduced the expression of K-Cadherin and increased the expression of connexin-43. These TGFß1-induced pro-fibrotic changes were attenuated by ASO5 treatment. 48 h after the removal of exogenous TGFß, further increases in αSMA, MMP2, MMP9 was observed; ASO5 significantly inhibited this subsequent increase. ASO5 treatment also significantly inhibited ability of the cell culture medium harvested at the end of the experiment (96h) to stimulate SMAD3 reporter cells. The role of endogenous TGFß1 was confirmed by the use of a TGFß receptor inhibitor. Our results demonstrate a critical role of FN EDA+ in a cycle of TGFß driven pro-fibrotic responses in human PTEC and blocking its production with ASO technology offers a potential therapy to interrupt this vicious circle and hence limit the progression of renal fibrosis.

Pet dogs succeed where human companions fail: The presence of pet dogs reduces pain.

Social support from family and friends, albeit associated with beneficial health effects, does not always help to cope with pain. This may be because humans elicit mixed expectations of social support and evaluative judgment. The present studies aimed to test whether pet dogs are a more beneficial source of support in a painful situation than human companions because they are not evaluative. For this, 74 (Study 1) and 50 (Study 2) women completed a cold-pressor task in the presence of either their own (S1) or an unfamiliar (S2) dog, a friend (S1), or an unknown human companion (S2), or alone. In both studies, participants reported less pain and exhibited less pain behavior in the presence of dogs compared to human companions. Reactions to pain were moderated by attitudes towards dogs in S2. This suggests that pet dogs may help individuals to cope with painful situations, especially if the individual in pain generally feels affectionate towards dogs.

Insight into C4 Selectivity in the Light-Driven C-H Fluoroalkylation of Pyridines and Quinolines.

Given the prevalence of pyridine motifs in FDA-approved drugs, selective fluoroalkylation of pyridines and quinolines is essential for preparing diverse bioisosteres. However, challenges are often faced with conventional Minisci reactions in achieving precise regioselectivity owing to competing reaction sites of pyridine and the limited availability of fluoroalkyl radical sources. Herein, we present a light-driven, C4-selective fluoroalkylation of azines utilizing N-aminopyridinium salts and readily available sulfinates. Our approach employs electron donor-acceptor complexes, achieving highly C4-selective fluoroalkylation under mild conditions without an external photocatalyst. This practical method not only enables the installation of CF2H groups but also allows for the incorporation of CF2-alkyl groups with diverse functional entities, surpassing the limitations of previous methods. The versatility of the radical pathway is further demonstrated through straightforward three-component reactions involving alkenes and [1.1.1]propellane. Detailed experimental and computational studies have elucidated the origins of regioselectivity, providing profound insights into the mechanistic aspects.

Assessment of Valance Emotional State Using EEG-EDA Coupling and Explainable Classifiers.

Emotion influences human life and impacts daily life activities. During emotional processes, physiological signals interact with each other instead of functioning separately. Although unimodal and multimodal approaches have been explored for emotion classification, there is a lack of inclusion of central and peripheral nervous system signal interaction-based approaches. In this study, an attempt has been made to characterize valance emotional states using Electroencephalogram (EEG)- Electrodermal activity (EDA) based coupling. For this, multimodal signals are obtained from the publicly available DEAP database (n=32 subjects). The EEG signals are decomposed into θ, α, ß, and bands and EDA signals are decomposed into phasic and tonic components. Then two EEG, three EDA, and two EEG-EDA coupling-based features are extracted and applied to three classifiers namely Random Forest (RF), Linear discriminant analysis, and Adaptive boosting. In addition, SHAP analysis is performed to explain classifiers' performance with respect to features. The result shows that the proposed approach is able to classify valence emotional states. The feature combination of EEG, EDA, and EEG-EDA coupling-based features with an RF classifier performs best with an F1-score of 68.21%. SHAP analysis in frontal electrodes with γ band obtained better discrimination among different valance states. This study underscores the significance of the coupling studies of EEG with EDA in classifying emotion. Therefore, the proposed approach can be extended to emotional state assessment in clinical settings.

Habituation of Central and Electrodermal Responses to an Auditory Two-Stimulus Oddball Paradigm.

The orienting reaction (OR) towards a new stimulus is subject to habituation, i.e., progressively attenuates with stimulus repetition. The skin conductance responses (SCRs) are known to represent a reliable measure of OR at the peripheral level. Yet, it is still a matter of debate which of the P3 subcomponents is the most likely to represent the central counterpart of the OR. The aim of the present work was to study habituation, recovery, and dishabituation phenomena intrinsic to a two-stimulus auditory oddball paradigm, one of the most-used paradigms both in research and clinic, by simultaneously recording SCRs and P3 in twenty healthy volunteers. Our findings show that the target stimulus was capable of triggering a more marked OR, as indexed by both SCRs and P3, compared to the standard stimulus, that could be due to its affective saliency and relevance for task completion; the application of temporal principal components analysis (PCA) to the P3 complex allowed us to identify several subcomponents including both early and late P3a (eP3a; lP3a), P3b, novelty P3 (nP3), and both a positive and a negative Slow Wave (+SW; -SW). Particularly, lP3a and P3b subcomponents showed a similar behavior to that observed for SCRs , suggesting them as central counterparts of OR. Finally, the P3 evoked by the first standard stimulus after the target showed a significant dishabituation phenomenon which could represent a sign of the local stimulus change. However, it did not reach a sufficient level to trigger an SCR/OR since it did not represent a salient event in the context of the task.

K-nearest neighbor based on exploratory data analysis of curriculum models of Chinese early childhood education.

This research examines the unique Chinese approaches to implementing the Early Childhood Curriculum (ECC) in Shenzhen and Hong Kong, drawing on School-based Curriculum Development (SBCD) studies. A total of 200 administrators and teachers were interviewed in total, and transcripts from those interviews were examined, cross-checked, and assessed using document analysis and classroom observation. Through interviews that have been conducted by administrators and teachers analyzed by document analysis and classroom observation, the influence of Chinese culture on ECC implementation is explored using the Cultural-Historical Activity Theory (CHAT). An exploratory, inferential, and descriptive statistical approach evaluates the sociocultural mechanism of ECC in Chinese society. The proposed framework utilizes K-Nearest Neighbor (KNN) regression analysis to illustrate how social development leads to cultural fusion and conflicts. The overall sociocultural framework promotes cultural growth and inheritance in China's early childhood education settings.

C-H Functionalization of Heteroarenes via Electron Donor-Acceptor Complex Photoactivation.

C-H Functionalization of heteroarenes stands as a potent instrument in organic synthesis, and with the incorporation of visible light, it emerged as a transformative game-changer. In this domain, electron donor-acceptor (EDA) complex, formed through the pairing of an electron-rich substrate with an electron-accepting molecule, has garnered substantial consideration in recent years due to the related avoidance of the requirement of photocatalyst as well as oxidant. EDA complexes can undergo photoactivation under mild conditions and exhibit high functional group tolerance, making them potentially suitable for the functionalization of biologically relevant heteroarenes. This review article provides an overview of recent advancements in the field of C-H functionalization of heteroarenes via EDA complex photoactivation with literature coverage up to April, 2024.

Chemistry of Cyclo[18]Carbon (C18): A Review.

Carbon-based allotropes are propelling a technological revolution in communication, sensing, and computing, concurrently challenging fundamental theories of the previous century. Nevertheless, the demand for advanced carbon-based materials remains substantial. The crux lies in the efficient and reliable engineering of novel carbon allotrope. Although C18 has undergone theoretical and experimental investigation for an extended period, its preparation and direct observation in the condensed phase occurred only recently through STM/AFM techniques. The distinctive cyclic ring structure and the dual 18-center π delocalization character introduce various uncommon properties to C18, rendering it a subject worthy of in-depth exploration. In this context, this review delves into past developments contributing to the state-of-the-art understanding of C18 and provides insights into how future endeavours can expedite practical applications. Encompassing a broad spectrum, this review comprehensively investigates almost all facets of C18, including geometric characteristics, electron delocalization, bonding nature, aromaticity, reactivity, electronic excitation, UV/Vis spectrum, intermolecular interaction, response to external fields, electron affinity, ionization, and other molecular properties. Moreover, the review also outlines representative strategies for the direct synthesis and characterization of C18 using atom manipulation techniques. Following this, C18-based complexes are summarized, and potential applications in catalysis, electrochemical devices, optoelectronics, and sensing are discussed.

Squamates as a model to understand key dental features of vertebrates.

Thanks to their exceptional diversity, teeth are among the most distinctive features of vertebrates. Parameters such as tooth size, shape, number, identity, and implantation can have substantial implications for the ecology and certain social behaviors of toothed species. Despite decades of research primarily focused on mammalian dentition, particularly using the laboratory mouse model, squamate reptiles ("lizards" and snakes) offer a wide array of tooth types and dentition variations. This diversity, which includes differences in size, shape, function, and replacement capacity, provides invaluable opportunities for investigating these fundamental properties. The central bearded dragon (Pogona vitticeps), a popular pet species with well-established husbandry practices, is of particular interest. It features a broad spectrum of morphs and spontaneous mutants and exhibits a wide range of heterodont phenotypes, including variation in the size, shape, number, implantation, and renewal of teeth at both posterior and anterior positions. These characteristics position the species as a crucial model organism for developmental studies in tooth research and for gaining deeper insights into evolutionary patterns of vertebrate dentitions. In this article, we provide an overview of the current understanding of squamate dentition, its diversity, development, and replacement. Furthermore, we discuss the significant advantages offered by squamate species as model organisms for investigating the evolutionary and developmental aspects of vertebrate dentition.

A General Photoactive H-Bonding EDA Complex Model Drives the Selective Hydrothiolation and Hydroxysulfenylation of Carbonyl Activated Alkenes.

Excitation of photoactive electron donor-acceptor (EDA) complexes to generate radical is a promising approach in radical chemistry. In this study, we introduce a new model of H-bonding EDA complexes for the selective hydrothiolation and hydroxysulfenylation of carbonyl-activated alkenes with diverse thiols under visible light conditions. The reliability of this H-bonding EDA complex model has been confirmed by meticulous experimental and theoretical calculations. Mechanistic investigations have revealed the significant influence of the solvent in determining whether the excitation of photoactive H-bonding EDA complex leads to charge transfer (CT) or energy-charge transfer (En-CT), thereby controlling Markovnikov and anti-Markovnikov selectivity. Notably, the Quantum Theory of Atoms in Molecules (QTAIM) analysis clearly shows that the excited state of the C=O-H-S EDA complex involves closed-shell partially covalent interactions.

Applying artificial intelligence on EDA sensor data to predict stress on minimally invasive robotic-assisted surgery.

PURPOSE: This study aims predicting the stress level based on the ergonomic (kinematic) and physiological (electrodermal activity-EDA, blood pressure and body temperature) parameters of the surgeon from their records collected in the previously immediate situation of a minimally invasive robotic surgery activity. METHODS: For this purpose, data related to the surgeon's ergonomic and physiological parameters were collected during twenty-six robotic-assisted surgical sessions completed by eleven surgeons with different experience levels. Once the dataset was generated, two preprocessing techniques were applied (scaled and normalized), these two datasets were divided into two subsets: with 80% of data for training and cross-validation, and 20% of data for test. Three predictive techniques (multiple linear regression-MLR, support vector machine-SVM and multilayer perceptron-MLP) were applied on training dataset to generate predictive models. Finally, these models were validated on cross-validation and test datasets. After each session, surgeons were asked to complete a survey of their feeling of stress. These data were compared with those obtained using predictive models. RESULTS: The results showed that MLR combined with the scaled preprocessing achieved the highest R2 coefficient and the lowest error for each parameter analyzed. Additionally, the results for the surgeons' surveys were highly correlated to the results obtained by the predictive models (R2 = 0.8253). CONCLUSIONS: The linear models proposed in this study were successfully validated on cross-validation and test datasets. This fact demonstrates the possibility of predicting factors that help us to improve the surgeon's health during robotic surgery.

Tumour-induced alterations in single-nucleus transcriptome of atrophying muscles indicate enhanced protein degradation and reduced oxidative metabolism.

BACKGROUND: Tumour-induced skeletal muscle wasting in the context of cancer cachexia is a condition with profound implications for patient survival. The loss of muscle mass is a significant clinical obstacle and is linked to reduced tolerance to chemotherapy and increased frailty. Understanding the molecular mechanisms driving muscle atrophy is crucial for the design of new therapeutics. METHODS: Lewis lung carcinoma tumours were utilized to induce cachexia and muscle atrophy in mice. Single-nucleus libraries of the tibialis anterior (TA) muscle from tumour-bearing mice and their non-tumour-bearing controls were constructed using 10X Genomics applications following the manufacturer's guidelines. RNA sequencing results were analysed with Cell Ranger software and the Seurat R package. Oxygen consumption of mitochondria isolated from TA muscle was measured using an Oroboros O2k-FluoRespirometer. Mouse primary myotubes were treated with a recombinant ectodysplasin A2 (EDA-A2) protein to activate EDA-A2 receptor (EDA2R) signalling and study changes in gene expression and oxygen consumption. RESULTS: Tumour-bearing mice were sacrificed while exhibiting moderate cachexia. Average TA muscle weight was reduced by 11% (P = 0.0207) in these mice. A total of 12 335 nuclei, comprising 6422 nuclei from the control group and 5892 nuclei from atrophying muscles, were studied. The analysis of single-nucleus transcriptomes identified distinct myonuclear gene signatures and a shift towards type IIb myonuclei. Muscle atrophy-related genes, including Atrogin1, MuRF1 and Eda2r, were upregulated in these myonuclei, emphasizing their crucial roles in muscle wasting. Gene set enrichment analysis demonstrated that EDA2R activation and tumour inoculation led to similar expression patterns in muscle cells, including the stimulation of nuclear factor-kappa B, Janus kinase-signal transducer and activator of transcription and transforming growth factor-beta pathways and the suppression of myogenesis and oxidative phosphorylation. Muscle oxidative metabolism was suppressed by both tumours and EDA2R activation. CONCLUSIONS: This study identified tumour-induced transcriptional changes in muscle tissue at single-nucleus resolution and highlighted the negative impact of tumours on oxidative metabolism. These findings contribute to a deeper understanding of the molecular mechanisms underlying muscle wasting.

Progress, applications, and challenges in high-throughput effect-directed analysis for toxicity driver identification - is it time for HT-EDA?

The rapid increase in the production and global use of chemicals and their mixtures has raised concerns about their potential impact on human and environmental health. With advances in analytical techniques, in particular, high-resolution mass spectrometry (HRMS), thousands of compounds and transformation products with potential adverse effects can now be detected in environmental samples. However, identifying and prioritizing the toxicity drivers among these compounds remain a significant challenge. Effect-directed analysis (EDA) emerged as an important tool to address this challenge, combining biotesting, sample fractionation, and chemical analysis to unravel toxicity drivers in complex mixtures. Traditional EDA workflows are labor-intensive and time-consuming, hindering large-scale applications. The concept of high-throughput (HT) EDA has recently gained traction as a means of accelerating these workflows. Key features of HT-EDA include the combination of microfractionation and downscaled bioassays, automation of sample preparation and biotesting, and efficient data processing workflows supported by novel computational tools. In addition to microplate-based fractionation, high-performance thin-layer chromatography (HPTLC) offers an interesting alternative to HPLC in HT-EDA. This review provides an updated perspective on the state-of-the-art in HT-EDA, and novel methods/tools that can be incorporated into HT-EDA workflows. It also discusses recent studies on HT-EDA, HT bioassays, and computational prioritization tools, along with considerations regarding HPTLC. By identifying current gaps in HT-EDA and proposing new approaches to overcome them, this review aims to bring HT-EDA a step closer to monitoring applications.

Diselenide-Bridged Mesoporous Silica-Based Nanoplatform with a Triple ROS-Scavenging Effect for Intracerebral Hemorrhage Treatment.

Oxidative stress (OS) is a major mediator of secondary brain injury following intracerebral hemorrhage (ICH). Thus, antioxidant therapy is emerging as an attractive strategy to combat ICH. To achieve both reactive oxygen species (ROS) scavenging ability and on-demand drug release ability, we constructed a novel polydopamine (PDA)-coated diselenide-bridged mesoporous silica nanoparticle (DSeMSN) drug delivery system (PDA-DSeMSN). Edaravone (Eda) was blocked in the pores of DSeMSN by covering the pores with PDA as a gatekeeper. The drug maintained nearly "zero release" before reaching the lesion site, while in the ROS-enriched circumstances, the PDA shell went through degradation and the doped diselenide bonds broke up, triggering the disintegration of nanoparticles and leading to Eda release. Interestingly, the ROS-degradable property of the PDA shell and diselenide bond endowed the system with enhanced ROS-eliminating capacity. The synergistic effect of ROS-responsive drug delivery and ROS-scavenging PDA-DSeMSN showed efficient antioxidative and mitochondria protective performance without apparent toxicity in vitro. Importantly, PDA-DSeMSN@Eda through intravenous administration specifically accumulated in perihematomal sites and demonstrated robust neuroprotection in an ICH mouse model through antioxidative and antiapoptotic effects with high biological safety. Thus, the PDA-DSeMSN platform holds tremendous potential as an excellent carrier for on-demand delivery of drugs and provides a new and effective strategy for the clinical treatment of ICH.

Edaravone combined with hyperbaric oxygen therapy in delayed encephalopathy after acute carbon monoxide poisoning: A meta-analysis.

BACKGROUND: The use of both edaravone (EDA) and hyperbaric oxygen therapy (HBOT) is increasingly prevalent in the treatment of delayed encephalopathy after carbon monoxide poisoning (DEACMP). This meta-analysis aims to evaluate the efficacy of using EDA and HBOT in combination with HBOT alone in the treatment of DEACMP. METHODS: We searched and included all randomized controlled trials (RCTs) published before November 6, 2023, from 12 Chinese and English databases and clinical trial centers in China and the United States. The main outcome indicator was the total effective rate. The secondary outcome indicators included the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), National Institutes of Health Stroke Scale (NIHSS), Barthel Index (BI), Hasegawa Dementia Scale (HDS), Fugl-Meyer Assessment (FMA), Superoxide Dismutase (SOD), and Malondialdehyde (MDA). Statistical measures utilized include risk ratios (RR), weighted mean difference (WMD), and 95 % confidence intervals (95 % CI). RESULTS: Thirty studies involving a combined total of 2075 participants were ultimately incorporated. It was observed that the combination of EDA with HBOT for the treatment of DEACMP demonstrated an improvement in the total effective rate (RR: 1.25; 95 % CI: 1.20-1.31; P < 0.01), MMSE (WMD: 3.67; 95 % CI: 2.59-4.76; P < 0.01), MoCA (WMD: 4.38; 95 % CI: 4.00-4.76; P < 0.01), BI (WMD: 10.94; 95 % CI: 5.23-16.66; P < 0.01), HDS (WMD: 6.80; 95 % CI: 4.05-9.55; P < 0.01), FMA (WMD: 8.91; 95 % CI: 7.22-10.60; P < 0.01), SOD (WMD: 18.45; 95 % CI: 16.93-19.98; P < 0.01); and a reduction in NIHSS (WMD: -4.12; 95 % CI: -4.93 to -3.30; P < 0.01) and MDA (WMD: -3.05; 95 % CI: -3.43 to -2.68; P < 0.01). CONCLUSION: Low-quality evidence suggests that for DEACMP, compared to using HBOT alone, the combined use of EDA and HBOT may be associated with better cognition and activity of daily living. In the future, conducting more meticulously designed multicenter and large-sample RCTs to substantiate our conclusions is essential.