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.

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.

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.

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.

A Novel Ectodysplasin a Gene mutation of X-Linked Hypohidrotic Ectodermal Dysplasia.

Introduction: Hypohidrotic ectodermal dysplasia (HED) is a genetic disorder that influences structures of ectodermal origin, such as teeth, hair, and sweat glands. Compared with autosomal recessive and dominant modes of inheritance, the X-linked HED (XLHED) characterized by Hypodontia/Oligodontia teeth, Absent/sparse hair, Anhidrosis/hypohidrosis, and characteristic facial features, is the most frequent and its primary cause is the mutation of ectodysplasin A (EDA) gene. This research aimed to expound the clinical and molecular features of a Chinese male with XLHED and to summarize and compare several previous findings. Methods: Genomic DNA was obtained from the peripheral blood of the proband and his family members, then Sanger sequencing was used to perform a mutational analysis of EDA. Real-time quantitative PCR and Western blotting were used to detect EDA expression. The transcriptional activity of NF-κB was detected using a luciferase assay. Results: The probandwith XLHED was identified a novel EDA mutation, c.1119G>C(p.M373I), that affected the molecular analysis of transmembrane protein exon8 mutations, inherited from the mother. He showed a severe multiple-tooth loss, with over 20 permanent teeth missing and sparse hair and eyebrows, dry, thin, and itching skin. Furthermore, his sweating function was abnormal to a certain extent. Discussion: The functional study showed that this novel mutant led to a significant decrease in the EDA expression level and transcriptional activity of NF-κB. Our findings extend the range of EDA mutations in XLHED patients, which provides the basis and idea for further exploring the pathogenesis of XLHED.

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.

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.

Target recycle initiated entropy driven assembly strategy for sensitive, enzyme-free, and portable miRNA detection.

MicroRNA (miRNA) is a pivotal biomarker in the diagnosis of various cancers, including bladder cancer (BCa). Despite their significance, the low abundance of miRNA presents a substantial challenge for sensitive and reliable detection. We introduce an innovative, highly sensitive assay for miRNA expression quantification that is both enzyme-free and portable. This method leverages the synergy of target recycling and entropy-driven assembly (EDA) for enhanced sensitivity and specificity. The proposed method possesses several advantages, including i) dual signal amplification through target recycling and EDA, which significantly boosts sensitivity with a lower limit of detection of 2.54 fM; ii) elimination of enzyme requirements, resulting in a cost-effective and stable signal amplification process; and iii) utilization of a personal glucose meter (PGM) for signal recording, rendering the method portable and adaptable to diverse settings. In summary, this PGM-based approach holds promising potential for clinical molecular diagnostics, offering a practical and efficient solution for miRNA analysis in cancer detection.

Expression of Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) Candidate Genes EDA2R, PCDH9, and TRAF7 in Normal Human Kidney Development and CAKUT.

Approximately half of the cases of chronic kidney disease (CKD) in childhood are caused by congenital anomalies of the kidney and urinary tract (CAKUT). Specific genes were identified as having significant importance in regard to the underlying genetic factors responsible for the CAKUT phenotype, and in our research, we focused on analyzing and comparing the expression levels of ectodysplasin A2 receptor (EDA2R), protocadherin9 (PCDH9), and TNF receptor-associated factor 7 (TRAF7) proteins in the cortex and medulla of healthy control kidneys during developmental phases 2, 3, and 4. We also performed an analysis of the area percentages of the mentioned proteins in the cortical and medullary sections of healthy embryonic and fetal kidneys compared to those affected by CAKUT, including duplex kidneys (DK), horseshoe kidneys (HK), hypoplastic kidneys (HYP), and dysplastic kidneys (DYS). We found that the CAKUT candidate gene proteins EDA2R, PCDH9, and TRAF7 are all expressed during normal human kidney development stages. In DYS, the expression of EDA2R was higher than in normal kidneys, likely due to EDA2R's role in apoptosis, which was upregulated in specific cases and could possibly contribute to the formation of DYS. The expression of PCDH9 was lower in HK, which can be attributed to the possible role of PCDH9 in cell migration suppression. Decreased PCDH9 expression is linked to increased cell migration, potentially contributing to the development of HK. The level of TRAF7 expression was reduced in all examined kidney disorders compared to normal kidneys, suggesting that this reduction might be attributed to the crucial role of TRAF7 in the formation of endothelium and ciliogenesis, both of which are essential for normal kidney development. Further research is required to ascertain the function of these proteins in both the typical development of the kidney and in CAKUT.

WheelSimPhysio-2023 dataset: Physiological and questionnaire-based dataset of immersive multisensory wheelchair simulator from 58 participants.

This data paper presents a unique multimodal dataset collected from a comprehensive experiment using a wheelchair training simulator. The dataset consists of quantitative and qualitative data that represents the user's experience and performance. Participants engaged in a series of navigational tasks in a simulated environment under two distinct system configuration conditions: a. a conventional monitor display and b. a virtual reality (VR) headset. The monitor group has a total of 24 participants data while using the simulator with a standard display and then other two groups of 18 and 16 respectively using the VR headset with a different wheelchair's speed profile. It was collected data from total of 58 participants. The dataset includes physiological data - Heart Rate Variability (HRV), Electrodermal Activity (EDA), Acceleration (ACC), Skin Temperature, Heart Rate (HR), and Blood Volume Pulse (BVP) - collected during both experiments. Additionally, for the standard display condition, more detailed data comprising Electroencephalography (EEG) and eye-tracking metrics were recorded to provide insights into cognitive load and visual attention patterns. System metrics captured from the simulator provide an objective performance report, including task completion times, error rates (collision of the virtual wheelchair), number of joystick commands. Also, the navigation efficiency data is complemented by post-experiment questionnaires, which gathered subjective responses on user experience, perceived difficulty, the user immersive levels, arousal, and simulator sickness symptoms. This dataset is valuable for researchers and practitioners in the fields of assistive technology, human-computer interaction, and rehabilitation. It offers metrics to a comprehensive view of how different display technologies influence the user experience in wheelchair simulation training. The data allows for in-depth analysis of physiological responses, cognitive engagement, and subjective perceptions, providing a foundation for future research on effective wheelchair training methodologies and the potential benefits of VR in rehabilitation settings.

A short simulated nature experience as an effective way to promote restoration from work-related stress.

Spending time in nature, and even watching images or videos of nature, has positive effects on one's mental state. However, cognitively stressful work is often performed indoors, in offices that lack easy access to nature during breaks. In this study, we investigated whether watching a 5-min audiovisual video that describes a first-person perspective walk on a forest path could help to restore one's mental state after cognitive stress. Participants were asked to perform cognitive stressor tasks, after which they were shown either a nature walk video or a control video. Subjective restoration was measured using self-reports before and after the videos, while electrodermal activity (EDA) and electroencephalography (EEG) were measured during the video-watching session. The results showed that experiencing the nature walk video enhanced subjective restoration more than watching the control video. Arousal of the autonomic nervous system, measured using EDA, decreased more during the nature walk video than during the control video. Additionally, activity in the EEG's upper theta band (6-8 Hz) and lower alpha band (8-10 Hz) increased during the nature walk video, suggesting that it induced a relaxed state of mind. Interestingly, the participants' connection with nature moderated the effects of the nature video. The subjective and physiological measures both suggest that watching a short, simulated nature walk may be beneficial in relaxing the mind and restoring one's mental state after cognitive stress.

High-Efficiency Effect-Directed Analysis Leveraging Five High Level Advancements: A Critical Review.

Organic contaminants are ubiquitous in the environment, with mounting evidence unequivocally connecting them to aquatic toxicity, illness, and increased mortality, underscoring their substantial impacts on ecological security and environmental health. The intricate composition of sample mixtures and uncertain physicochemical features of potential toxic substances pose challenges to identify key toxicants in environmental samples. Effect-directed analysis (EDA), establishing a connection between key toxicants found in environmental samples and associated hazards, enables the identification of toxicants that can streamline research efforts and inform management action. Nevertheless, the advancement of EDA is constrained by the following factors: inadequate extraction and fractionation of environmental samples, limited bioassay endpoints and unknown linkage to higher order impacts, limited coverage of chemical analysis (i.e., high-resolution mass spectrometry, HRMS), and lacking effective linkage between bioassays and chemical analysis. This review proposes five key advancements to enhance the efficiency of EDA in addressing these challenges: (1) multiple adsorbents for comprehensive coverage of chemical extraction, (2) high-resolution microfractionation and multidimensional fractionation for refined fractionation, (3) robust in vivo/vitro bioassays and omics, (4) high-performance configurations for HRMS analysis, and (5) chemical-, data-, and knowledge-driven approaches for streamlined toxicant identification and validation. We envision that future EDA will integrate big data and artificial intelligence based on the development of quantitative omics, cutting-edge multidimensional microfractionation, and ultraperformance MS to identify environmental hazard factors, serving for broader environmental governance.

Visible-Light-Driven Germyl Radical Generation via EDA-Catalyzed ET-HAT Process.

We have established a facile and efficient protocol for the generation of germyl radicals by employing photo-excited electron transfer (ET) in an electron donor-acceptor (EDA) complex to drive hydrogen-atom transfer (HAT) from germyl hydride (R3GeH). Using a catalytic amount of EDA complex of commercially available thiol and benzophenone derivatives, the ET-HAT cycle smoothly proceeds simply upon blue-light irradiation without any transition metal or photocatalyst. This protocol also affords silyl radical from silyl hydride.

Human Activity Recognition Algorithm with Physiological and Inertial Signals Fusion: Photoplethysmography, Electrodermal Activity, and Accelerometry.

Inertial signals are the most widely used signals in human activity recognition (HAR) applications, and extensive research has been performed on developing HAR classifiers using accelerometer and gyroscope data. This study aimed to investigate the potential enhancement of HAR models through the fusion of biological signals with inertial signals. The classification of eight common low-, medium-, and high-intensity activities was assessed using machine learning (ML) algorithms, trained on accelerometer (ACC), blood volume pulse (BVP), and electrodermal activity (EDA) data obtained from a wrist-worn sensor. Two types of ML algorithms were employed: a random forest (RF) trained on features; and a pre-trained deep learning (DL) network (ResNet-18) trained on spectrogram images. Evaluation was conducted on both individual activities and more generalized activity groups, based on similar intensity. Results indicated that RF classifiers outperformed corresponding DL classifiers at both individual and grouped levels. However, the fusion of EDA and BVP signals with ACC data improved DL classifier performance compared to a baseline DL model with ACC-only data. The best performance was achieved by a classifier trained on a combination of ACC, EDA, and BVP images, yielding F1-scores of 69 and 87 for individual and grouped activity classifications, respectively. For DL models trained with additional biological signals, almost all individual activity classifications showed improvement (p-value < 0.05). In grouped activity classifications, DL model performance was enhanced for low- and medium-intensity activities. Exploring the classification of two specific activities, ascending/descending stairs and cycling, revealed significantly improved results using a DL model trained on combined ACC, BVP, and EDA spectrogram images (p-value < 0.05).

EDA2R knockdown alleviates myocardial ischemia/reperfusion injury through inhibiting the activation of the NF-κB signaling pathway.

Ischemia/reperfusion (I/R) is a pathological process that occurs in numerous organs and is often associated with severe cellular damage and death. Ectodysplasin-A2 receptor (EDA2R) is a member of the TNF receptor family that has anti-inflammatory and antioxidant effects. However, to the best of our knowledge, its role in the progression of myocardial I/R injury remains unclear. The present study aimed to investigate the role of EDA2R during myocardial I/R injury and the molecular mechanisms involved. In vitro, dexmedetomidine (DEX) exhibited a protective effect on hypoxia/reoxygenation (H/R)-induced cardiomyocyte injury and downregulated EDA2R expression. Subsequently, EDA2R silencing enhanced cell viability and reduced the apoptosis of cardiomyocytes. Furthermore, knockdown of EDA2R led to an elevated mitochondrial membrane potential (MMP), repressed the release of Cytochrome C and upregulated Bcl-2 expression. EDA2R knockdown also resulted in downregulated expression of Bax, and decreased activity of Caspase-3 and Caspase-9 in cardiomyocytes, reversing the effects of H/R on mitochondria-mediated apoptosis. In addition, knockdown of EDA2R suppressed H/R-induced oxidative stress. Mechanistically, EDA2R knockdown inactivated the NF-κB signaling pathway. Additionally, downregulation of EDA2R weakened myocardial I/R injury in mice, as reflected by improved left ventricular function and reduced infarct size, as well as suppressed apoptosis and oxidative stress. Additionally, EDA2R knockdown repressed the activation of NF-κB signal in vivo. Collectively, knockdown of EDA2R exerted anti-apoptotic and antioxidant effects against I/R injury in vivo and in vitro by suppressing the NF-κB signaling pathway.

Lateral asymmetry of emotional arousal as a biomarker of attributional style during darts competitions.

According to the Multiple Arousal Theory, electrodermal activity (EDA) is not uniform across the body. However, the psychological meaning of a left or right-sided EDA dominance is still not clear. We explored EDA lateral asymmetry as a psychophysiological marker of optimistic and pessimistic attributional style regarding success and failure in a darts competition. Bilateral EDA pattern of 230 throws of a competing pair was measured by Obimon EDA including accelerometer measurements of movements. First, we confirmed that lateral asymmetry can be measured reliably based on EDA data from both wrists. Second, we assessed attributional styles related to lateral asymmetry based on 80 individual throws. We recorded participants' expectations regarding their upcoming performance, and their attribution of success and failure based on Seligman's definition as optimist (internal cause attributed to success, or external cause ascribed to failure) or pessimist. The ratio of optimist and pessimist attributions was significantly different for throws with right or left-sided EDA dominance (p = 0.001). Optimistic attribution characterized 84% of right dominant, while pessimist 63% of left-dominant EDA during throws. We replicated these findings on 50 throws from 10 more individuals (p = 0.034). All individuals were right-handed. We conclude that wrist EDA can be reliably measured during physical movements, such as in a darts game. Lateral EDA asymmetry is a consistent psychophysiological marker of the attitude toward success and failure in a competitive setting, suggesting that lateral asymmetry of emotional arousal may serve as a novel psychophysiological biomarker for attribution style. Results underlie the psychophysiological relevance of bilateral arousal assessment and provide evidence-based verification for the Multiple Arousal Theory.

A new approach for environmental damage assessment pursuant to the European Union Environmental Liability Directive.

The European Union and Member States national laws require competent authorities to promptly and effectively address environmental incidents, noncompliances, and criminal offenses, necessitating thorough planning of investigation and assessment activities. To enhance environmental damage assessments in line with the European Environmental Liability Directive (ELD, 2004/35/EC), the European Union Network for the Implementation and Enforcement of Environmental Law (IMPEL Network) has introduced the Criteria for the Assessment of the Environmental Damage (CAED) framework. This framework, outlined in a Practical Guide, offers a methodological approach to environmental damage assessment (EDA) focusing on three key objectives: case screening, identification of "clues" of damage, and determination of "evidence" of damage. Given the critical importance of structured data collection and evaluation, the CAED project has adopted a Driver, Pressure, State, Impact, and Response (DPSIR) model adapted to environmental damage and developed the Practical Tables. These tables serve as a comprehensive tool for systematically identifying investigative priorities and collecting standardized data and information using a predefined list of qualitative or quantitative indicators. This article provides an overview of the Practical Guide and Practical Tables, collectively referred to as the CAED Toolkit, aiming to establish a common framework for environmental damage assessments among various competent authorities and stakeholders across Europe. Integr Environ Assess Manag 2024;00:1-10. © 2024 SETAC.

Multiple Bonding in AeN- (Ae=Ca, Sr, Ba).

Quantum chemical calculations using ab initio methods at the MRCI+Q(8,9)/def2-QZVPPD and CCSD(T)/def2-QZVPPD levels as well as using density functional theory are reported for the diatomic molecules AeN- (Ae=Ca, Sr, Ba). The anions CaN- and SrN- have electronic triplet (3Π) ground states with nearly identical bond dissociation energies De ~57 kcal/mol calculated at the MRCI+Q(8,9)/def2-QZVPPD level. In contrast, the heavier homologue BaN- has a singlet (1Σ+) ground state, which is only 1.1 kcal/mol below the triplet (3Σ-) state. The computed bond dissociation energy of (1Σ+) BaN- is 68.4 kcal/mol. The calculations at the CCSD(T)-full/def2-QZVPPD and BP86-D3(BJ)/def2-QZVPPD levels are in reasonable agreement with the MRCI+Q(8,9)/def2-QZVPPD data, except for the singlet (1Σ+) state, which has a large multireference character. The calculated atomic partial charges given by the CM5, Voronoi and Hirshfeld methods suggest small to medium-sized Ae←N- charge donation for most electronic states. In contrast, the NBO method predicts for all species medium to large Ae→N- electronic charge donation, which is due to the neglect of the (n)p AOs of Ae atoms as genuine valence orbitals. Neither the bond orders nor the bond lengths correlate with the bond dissociation energies. The EDA-NOCV calculations show that the heavier alkaline earth atoms Ca, Sr, Ba use their (n)s and (n-1)d orbitals for covalent bonding.

Characterization of age-associated gene expression changes in mouse sweat glands.

Evaporation of sweat on the skin surface is the major mechanism for dissipating heat in humans. The secretory capacity of sweat glands (SWGs) declines during aging, leading to heat intolerance in the elderly, but the mechanisms responsible for this decline are poorly understood. We investigated the molecular changes accompanying SWG aging in mice, where sweat tests confirmed a significant reduction of active SWGs in old mice relative to young mice. We first identified SWG-enriched mRNAs by comparing the skin transcriptome of Eda mutant Tabby male mice, which lack SWGs, with that of wild-type control mice by RNA-sequencing analysis. This comparison revealed 171 mRNAs enriched in SWGs, including 47 mRNAs encoding 'core secretory' proteins such as transcription factors, ion channels, ion transporters, and trans-synaptic signaling proteins. Among these, 28 SWG-enriched mRNAs showed significantly altered abundance in the aged male footpad skin, and 11 of them, including Foxa1, Best2, Chrm3, and Foxc1 mRNAs, were found in the 'core secretory' category. Consistent with the changes in mRNA expression levels, immunohistology revealed that higher numbers of secretory cells from old SWGs express the transcription factor FOXC1, the protein product of Foxc1 mRNA. In sum, our study identified mRNAs enriched in SWGs, including those that encode core secretory proteins, and altered abundance of these mRNAs and proteins with aging in mouse SWGs.