A general approach for inferring the ancestry of recent ancestors of an admixed individual.

The genome of an individual from an admixed population consists of segments originated from different ancestral populations. Most existing ancestry inference approaches focus on calling these segments for the extant individual. In this paper, we present a general ancestry inference approach for inferring recent ancestors from an extant genome. Given the genome of an individual from a recently admixed population, our method can estimate the proportions of the genomes of the recent ancestors of this individual that originated from some ancestral populations. The key step of our method is the inference of ancestors (called founders) right after the formation of an admixed population. The inferred founders can then be used to infer the ancestry of recent ancestors of an extant individual. Our method is implemented in a computer program called PedMix2. To the best of our knowledge, there is no existing method that can practically infer ancestors beyond grandparents from an extant individual's genome. Results on both simulated and real data show that PedMix2 performs well in ancestry inference.

Orchestrating information across tissues via a novel multitask GAT framework to improve quantitative gene regulation relation modeling for survival analysis.

Survival analysis is critical to cancer prognosis estimation. High-throughput technologies facilitate the increase in the dimension of genic features, but the number of clinical samples in cohorts is relatively small due to various reasons, including difficulties in participant recruitment and high data-generation costs. Transcriptome is one of the most abundantly available OMIC (referring to the high-throughput data, including genomic, transcriptomic, proteomic and epigenomic) data types. This study introduced a multitask graph attention network (GAT) framework DQSurv for the survival analysis task. We first used a large dataset of healthy tissue samples to pretrain the GAT-based HealthModel for the quantitative measurement of the gene regulatory relations. The multitask survival analysis framework DQSurv used the idea of transfer learning to initiate the GAT model with the pretrained HealthModel and further fine-tuned this model using two tasks i.e. the main task of survival analysis and the auxiliary task of gene expression prediction. This refined GAT was denoted as DiseaseModel. We fused the original transcriptomic features with the difference vector between the latent features encoded by the HealthModel and DiseaseModel for the final task of survival analysis. The proposed DQSurv model stably outperformed the existing models for the survival analysis of 10 benchmark cancer types and an independent dataset. The ablation study also supported the necessity of the main modules. We released the codes and the pretrained HealthModel to facilitate the feature encodings and survival analysis of transcriptome-based future studies, especially on small datasets. The model and the code are available at http://www.healthinformaticslab.org/supp/.

Advancing Ligand Docking through Deep Learning: Challenges and Prospects in Virtual Screening.

Molecular docking, also termed ligand docking (LD), is a pivotal element of structure-based virtual screening (SBVS) used to predict the binding conformations and affinities of protein-ligand complexes. Traditional LD methodologies rely on a search and scoring framework, utilizing heuristic algorithms to explore binding conformations and scoring functions to evaluate binding strengths. However, to meet the efficiency demands of SBVS, these algorithms and functions are often simplified, prioritizing speed over accuracy.The emergence of deep learning (DL) has exerted a profound impact on diverse fields, ranging from natural language processing to computer vision and drug discovery. DeepMind's AlphaFold2 has impressively exhibited its ability to accurately predict protein structures solely from amino acid sequences, highlighting the remarkable potential of DL in conformation prediction. This groundbreaking advancement circumvents the traditional search-scoring frameworks in LD, enhancing both accuracy and processing speed and thereby catalyzing a broader adoption of DL algorithms in binding pose prediction. Nevertheless, a consensus on certain aspects remains elusive.In this Account, we delineate the current status of employing DL to augment LD within the VS paradigm, highlighting our contributions to this domain. Furthermore, we discuss the challenges and future prospects, drawing insights from our scholarly investigations. Initially, we present an overview of VS and LD, followed by an introduction to DL paradigms, which deviate significantly from traditional search-scoring frameworks. Subsequently, we delve into the challenges associated with the development of DL-based LD (DLLD), encompassing evaluation metrics, application scenarios, and physical plausibility of the predicted conformations. In the evaluation of LD algorithms, it is essential to recognize the multifaceted nature of the metrics. While the accuracy of binding pose prediction, often measured by the success rate, is a pivotal aspect, the scoring/screening power and computational speed of these algorithms are equally important given the pivotal role of LD tools in VS. Regarding application scenarios, early methods focused on blind docking, where the binding site is unknown. However, recent studies suggest a shift toward identifying binding sites rather than solely predicting binding poses within these models. In contrast, LD with a known pocket in VS has been shown to be more practical. Physical plausibility poses another significant challenge. Although DLLD models often achieve higher success rates compared to traditional methods, they may generate poses with implausible local structures, such as incorrect bond angles or lengths, which are disadvantageous for postprocessing tasks like visualization. Finally, we discuss the future perspectives for DLLD, emphasizing the need to improve generalization ability, strike a balance between speed and accuracy, account for protein conformation flexibility, and enhance physical plausibility. Additionally, we delve into the comparison between generative and regression algorithms in this context, exploring their respective strengths and potential.

Decoding Endothelial MPL and JAK2V617F Mutation: Insight Into Cardiovascular Dysfunction in Myeloproliferative Neoplasms.

BACKGROUND: Patients with JAK2V617F-positive myeloproliferative neoplasms (MPNs) and clonal hematopoiesis of indeterminate potential face a significantly elevated risk of cardiovascular diseases. Endothelial cells carrying the JAK2V617F mutation have been detected in many patients with MPN. In this study, we investigated the molecular basis for the high incidence of cardiovascular complications in patients with MPN. METHODS: We investigated the impact of endothelial JAK2V617F mutation on cardiovascular disease development using both transgenic murine models and MPN patient-derived induced pluripotent stem cell lines. RESULTS: Our investigations revealed that JAK2V617F mutant endothelial cells promote cardiovascular diseases under stress, which is associated with endothelial-to-mesenchymal transition and endothelial dysfunction. Importantly, we discovered that inhibiting the endothelial TPO (thrombopoietin) receptor MPL (myeloproliferative leukemia virus oncogene) suppressed JAK2V617F-induced endothelial-to-mesenchymal transition and prevented cardiovascular dysfunction caused by mutant endothelial cells. Notably, the endothelial MPL receptor is not essential for the normal physiological regulation of blood cell counts and cardiac function. CONCLUSIONS: JAK2V617F mutant endothelial cells play a critical role in the development of cardiovascular diseases in JAK2V617F-positive MPNs, and endothelial MPL could be a promising therapeutic target for preventing or ameliorating cardiovascular complications in these patients.

Proteomic Profiling Reveals the Molecular Control of Oocyte Maturation.

Meiotic maturation is an intricate and precisely regulated process orchestrated by various pathways and numerous proteins. However, little is known about the proteome landscape during oocytes maturation. Here, we obtained the temporal proteomic profiles of mouse oocytes during in vivo maturation. We successfully quantified 4694 proteins from 4500 oocytes in three key stages (germinal vesicle, germinal vesicle breakdown, and metaphase II). In particular, we discovered the novel proteomic features during oocyte maturation, such as the active Skp1-Cullin-Fbox pathway and an increase in mRNA decay-related proteins. Using functional approaches, we further identified the key factors controlling the histone acetylation state in oocytes and the vital proteins modulating meiotic cell cycle. Taken together, our data serve as a broad resource on the dynamics occurring in oocyte proteome and provide important knowledge to better understand the molecular mechanisms during germ cell development.

Multi-Shell Nanourchin-Integrated Dual Mode Lateral Flow Immunoassay for Sensitive and Rapid Detection of Clinical Cardiac Myosin-Binding Protein C.

Cardiac myosin-binding protein C (cMyBP-C) is a novel cardiac marker of acute myocardial infarction (AMI) and acute cardiac injuries (ACI). Construction of point-of-care testing techniques capable of sensing cMyBP-C with high sensitivity and precision is urgently needed. Herein, we synthesized an Au@NGQDs@Au/Ag multi-shell nanoUrchins (MSNUs), and then applied it in a colorimetric/SERS dual-mode immunoassay for detection of cMyBP-C. The MSNUs displayed superior stability, colorimetric brightness, and SERS enhancement ability with an enhanced factor of 5.4 × 109, which were beneficial to improve the detection capability of test strips. The developed MSNU-based test strips can achieve an ultrasensitive immunochromatographic assay of cMyBP-C in both colorimetric and SERS modes with the limits of detection as low as 19.3 and 0.77 pg/mL, respectively. Strikingly, this strip was successfully applied to analyze actual plasma samples with significantly better sensitivity, negative predictive value, and accuracy than commercially available gold test strips. Notably, this method possessed a wide range of application scenarios via combining with a color recognizer application named Color Grab on the smartphone, which can meet various needs of different users. Overall, our MSNU-based test strip as a mobile health monitoring tool shows excellent sensitivity, reproducibility, and rapid detection of the cMyBP-C, which holds great potential for the early clinic diagnosis of AMI and ACI.

Rationale and design of a single-center randomized trial to compare the graft patency between the radial artery and the no-touch saphenous vein in coronary artery bypass grafting surgery (GRAFT-CAB Study).

BACKGROUND: Previous studies suggested only the radial artery and the No-touch (NT) technique were effective in reducing graft occlusion after coronary artery bypass grafting (CABG) surgery. However, there is no randomized trial comparing these 2 graft conduits. The optimum second conduit for CABG remains undetermined. MATERIALS AND METHODS: This study is a prospective, single-center randomized clinical trial, aiming to compare the graft patency between the radial artery and the NT vein graft. All patients undergoing isolated CABG with left internal mammary artery (LIMA) plus at least 2 additional grafts will be considered eligible. About 774 cases (516 in the radial artery group and 258 in the NT vein group) will be enrolled in over 1 to 2 years. Participants will be randomized and allocated to two bypass strategies: the LIMA plus 1 radial artery and 1 conventional vein graft, or the LIMA plus 2 NT vein grafts. The primary outcome is graft occlusion at 1 year after CABG evaluated by CT angiography. The secondary outcomes include graft occlusion at 3 and 5 years and major adverse cardiac or cerebrovascular events at 1, 3, and 5 years follow-ups. DISCUSSION: This study will define whether or not the NT vein has a lower graft occlusion rate than the radial artery in short and mid-term follow-ups, and provide new evidence for the second conduit choice in CABG surgery. TRIAL REGISTRATION: ClinicalTrials.gov NCT06014047. Registered on October 15th, 2023.

High-reliability infrared broadband thin-film polarizing beam splitter with ZnSe compensation layers.

Thin-film polarizing beam splitters (PBSs) fulfill a pivotal role in laser beam splitting, modulation, shaping and isolation. In this study, a high-reliability infrared broadband thin-film PBS was developed. To correct for tensile stress in Ge/YbF3 multilayer coatings, ZnSe compensation layers were incorporated in the multilayer design. The effects of different symmetrical periods on the spectral properties of the infrared PBS were systematically discussed. The infrared PBS operated at 45° and in the long-wave infrared (LWIR) band. Using the percent of optical extrema monitoring (POEM) strategy combined with the high-temperature optical constants (HTOC) of Ge film, the infrared PBS was precisely fabricated on ZnSe substrates. Subsequently, the spectral performance and film reliability of the infrared PBS were carefully characterized. Specifically, the transmittance of p-polarization surpassed 96%, while the extinction ratio exceeded 100:1 within the 10.6 ± 0.15 µm band. The infrared PBS demonstrated commendable environmental reliability, in addition to exhibiting excellent spectral characteristics.

2 × 2 MIMO dual spiral octagonal prism liquid DRA with snake-shaped DGS for OAM multiplexing.

In this paper, we proposed a 2 × 2 multiple-input multiple-output (MIMO) dual spiral octagonal prism liquid dielectric resonator antenna (DRA) with snake-shaped defective ground structure (DGS) for space multiplexing of orbital angular momentum (OAM). The DRA element adopts an inner and outer nested dual spiral structure filled with 0.035 g/ml of brine outside and a cylinder filled with distilled water inside. The proposed MIMO antenna can generate resonance at 1.78-3.02 GHz and 4.01-7.73 GHz (S11≤-10 dB). The isolation among ports is below -20 dB at 2.6 GHz and below -40 dB at 5.1 GHz, which can effectively isolate the l = ±1 and l = ±3 modes' OAM waves through the snake-shaped DGS. The proposed MIMO antenna improves spectral efficiency by OAM spatial multiplexing with l = ±1 and l = ±3 modes' OAM, which improves the data transmission efficiency. The proposed MIMO antenna provides a novel, to the best of our knowledge, solution for wireless communications to improve spectral efficiency.

Echelon grating refractive index sensor.

There are few reports on optical refractive index sensors that have both high resonant-wavelength resolution (RWR) and high refractive index sensitivity (RIS). Herein, based on an echelon grating, we design a refractive index sensor that combines the two advantages together. The principal fringe of echelon grating has a small full width at half maximum and a good signal-to-noise ratio, leading to a high RWR. The wavefront splitting interference makes the sensor have high RIS. The large free spectral range (FSR) of the principal fringes expands the dynamic range of the sensor. The experimentally realized RWR, RIS, and FSR are 2 × 10-2 nm, 1.14 × 104 nm/RIU (RIU: refractive index unit), and 130 nm, respectively. The detection limit of refractive index is 1.59 × 10-6 RIU. The dynamic range of the sensor is 1.14 × 10-2 RIU. In addition, there are schemes to improve RWR and RIS, which can further reduce the detection limit of refractive index. The echelon grating refractive index sensor features low detection limit, low cost, high stability, and good robustness.

Detection of MicroRNA-155 based on lambda exonuclease selective digestion and CRISPR/cas12a-assisted amplification.

In numerous malignancies, miRNA-155 is overexpressed and has oncogenic activity because it is one of the most efficient microRNAs for inhibiting apoptosis in human cancer cells. As a result, the highest sensitive detection of the miRNA-155 gene is a technological instrument that can enable early cancer screening. In this study, a miRNA-155 biosensor was created to create a hairpin probe that can bind to the miRNA-155 gene using lambda nucleic acid exonuclease, which can cut the 5' phosphorylated double strand, and by the DNA probe is recognized by the Cas12a enzyme, which then activates Cas12a to catalyze trans-cutting produces strong fluorescence. Research finding, the target concentration's logarithm and corresponding fluorescence intensity have a strong linear connection, and the limit of detection (LOD) of the sensing system was determined to be 8.3 pM. In addition, the biosensor displayed exceptional specificity, low false-positive signal, and high sensitivity in detecting the miRNA-155 gene in serum samples. This study's creation of a biosensor that has high sensitivity, good selectivity, and is simple to operate provides promising opportunities for research into biosensor design and early cancer detection.

GANSamples-ac4C: Enhancing ac4C site prediction via generative adversarial networks and transfer learning.

RNA modification, N4-acetylcytidine (ac4C), is enzymatically catalyzed by N-acetyltransferase 10 (NAT10) and plays an essential role across tRNA, rRNA, and mRNA. It influences various cellular functions, including mRNA stability and rRNA biosynthesis. Wet-lab detection of ac4C modification sites is highly resource-intensive and costly. Therefore, various machine learning and deep learning techniques have been employed for computational detection of ac4C modification sites. The known ac4C modification sites are limited for training an accurate and stable prediction model. This study introduces GANSamples-ac4C, a novel framework that synergizes transfer learning and generative adversarial network (GAN) to generate synthetic RNA sequences to train a better ac4C modification site prediction model. Comparative analysis reveals that GANSamples-ac4C outperforms existing state-of-the-art methods in identifying ac4C sites. Moreover, our result underscores the potential of synthetic data in mitigating the issue of data scarcity for biological sequence prediction tasks. Another major advantage of GANSamples-ac4C is its interpretable decision logic. Multi-faceted interpretability analyses detect key regions in the ac4C sequences influencing the discriminating decision between positive and negative samples, a pronounced enrichment of G in this region, and ac4C-associated motifs. These findings may offer novel insights for ac4C research. The GANSamples-ac4C framework and its source code are publicly accessible at http://www.healthinformaticslab.org/supp/.

Protective factors for children with autism spectrum disorder during COVID-19-related strict lockdowns: a Shanghai autism early developmental cohort study.

BACKGROUND: COVID-19 lockdowns increased the risk of mental health problems, especially for children with autism spectrum disorder (ASD). However, despite its importance, little is known about the protective factors for ASD children during the lockdowns. METHODS: Based on the Shanghai Autism Early Developmental Cohort, 188 ASD children with two visits before and after the strict Omicron lockdown were included; 85 children were lockdown-free, while 52 and 51 children were under the longer and the shorter durations of strict lockdown, respectively. We tested the association of the lockdown group with the clinical improvement and also the modulation effects of parent/family-related factors on this association by linear regression/mixed-effect models. Within the social brain structures, we examined the voxel-wise interaction between the grey matter volume and the identified modulation effects. RESULTS: Compared with the lockdown-free group, the ASD children experienced the longer duration of strict lockdown had less clinical improvement (ß = 0.49, 95% confidence interval (CI) [0.19-0.79], p = 0.001) and this difference was greatest for social cognition (2.62 [0.94-4.30], p = 0.002). We found that this association was modulated by parental agreeableness in a protective way (-0.11 [-0.17 to -0.05], p = 0.002). This protective effect was enhanced in the ASD children with larger grey matter volumes in the brain's mentalizing network, including the temporal pole, the medial superior frontal gyrus, and the superior temporal gyrus. CONCLUSIONS: This longitudinal neuroimaging cohort study identified that the parental agreeableness interacting with the ASD children's social brain development reduced the negative impact on clinical symptoms during the strict lockdown.

Facile Friedel-Crafts alkylation of arenes under solvent-free conditions.

The Friedel-Crafts alkylation of arenes is an important part of electrophilic aromatic substitution reactions. However, the reactivity of arenes is weakened by electron-withdrawing substituents, leading to limited substrate scopes and applications. Herein, we developed an efficient HOTf-promoted Friedel-Crafts alkylation reaction of broad arenes with α-aryl-α-diazoesters under metal-free and solvent-free conditions.

Assessing the performance of MM/PBSA and MM/GBSA methods. 10. Prediction reliability of binding affinities and binding poses for RNA-ligand complexes.

Ribonucleic acid (RNA)-ligand interactions play a pivotal role in a wide spectrum of biological processes, ranging from protein biosynthesis to cellular reproduction. This recognition has prompted the broader acceptance of RNA as a viable candidate for drug targets. Delving into the atomic-scale understanding of RNA-ligand interactions holds paramount importance in unraveling intricate molecular mechanisms and further contributing to RNA-based drug discovery. Computational approaches, particularly molecular docking, offer an efficient way of predicting the interactions between RNA and small molecules. However, the accuracy and reliability of these predictions heavily depend on the performance of scoring functions (SFs). In contrast to the majority of SFs used in RNA-ligand docking, the end-point binding free energy calculation methods, such as molecular mechanics/generalized Born surface area (MM/GBSA) and molecular mechanics/Poisson Boltzmann surface area (MM/PBSA), stand as theoretically more rigorous approaches. Yet, the evaluation of their effectiveness in predicting both binding affinities and binding poses within RNA-ligand systems remains unexplored. This study first reported the performance of MM/PBSA and MM/GBSA with diverse solvation models, interior dielectric constants (εin) and force fields in the context of binding affinity prediction for 29 RNA-ligand complexes. MM/GBSA is based on short (5 ns) molecular dynamics (MD) simulations in an explicit solvent with the YIL force field; the GBGBn2 model with higher interior dielectric constant (εin = 12, 16 or 20) yields the best correlation (Rp = -0.513), which outperforms the best correlation (Rp = -0.317, rDock) offered by various docking programs. Then, the efficacy of MM/GBSA in identifying the near-native binding poses from the decoys was assessed based on 56 RNA-ligand complexes. However, it is evident that MM/GBSA has limitations in accurately predicting binding poses for RNA-ligand systems, particularly compared with notably proficient docking programs like rDock and PLANTS. The best top-1 success rate achieved by MM/GBSA rescoring is 39.3%, which falls below the best results given by docking programs (50%, PLNATS). This study represents the first evaluation of MM/PBSA and MM/GBSA for RNA-ligand systems and is expected to provide valuable insights into their successful application to RNA targets.

Mitochondrial KATP channel-mediated autophagy contributes to angiotensin II-induced vascular dysfunction in mice.

BACKGROUND AND AIM: The present study aimed to investigate whether the mitochondrial KATP channel contributes to angiotensin II (Ang II)-induced vascular dysfunction, the development of hypertension, and atherosclerosis. METHODS AND RESULTS: ApoE (-/-) mice fed a high-fat diet were chronically infused with Ang II for eight weeks and concomitantly treated with losartan (ARB), apocynin, or 5-hydroxy decanoate (5-HD), or 3-methyladenine (3-MA). Systolic blood pressure was measured, and pathological changes of aortic or liver tissue were observed. Nitric oxide (NO), superoxide dismutase 2 (SOD2) levels and vasorelaxation rate were measured, and protein and mRNA expressions were examined by western blot and RT-PCR. Ang II-induced development of hypertension was suppressed not only by ARB, and apocynin but also by 5-HD or 3-MA. Ang II infusion decreased aortic NO production and relaxation, as well as SOD2 activity in liver, which were improved by all treatments. In addition, Ang II-induced activation of autophagy was suppressed by 5-HD in aortic tissue, furthermore, Ang II increases the atherosclerotic index in plasma and exacerbates the development of atherosclerosis by increases of fat deposition in the aorta and liver. Lipid metabolism-related mRNA expressions (LXR-α, LDLR, SRBI, Acca, and FASN) were changed by Ang II. Similarly, not only ARB, and apocynin, but also 5-HD and 3-MA suppressed Ang II-induced these changes. CONCLUSIONS: Our present findings evidence that mitochondrial KATP channel-mediated autophagy contributes to Ang II-induced vascular dysfunction, development of hypertension, and atherosclerosis.

MRI reconstruction with enhanced self-similarity using graph convolutional network.

BACKGROUND: Recent Convolutional Neural Networks (CNNs) perform low-error reconstruction in fast Magnetic Resonance Imaging (MRI). Most of them convolve the image with kernels and successfully explore the local information. Nonetheless, the non-local image information, which is embedded among image patches relatively far from each other, may be lost due to the limitation of the receptive field of the convolution kernel. We aim to incorporate a graph to represent non-local information and improve the reconstructed images by using the Graph Convolutional Enhanced Self-Similarity (GCESS) network. METHODS: First, the image is reconstructed into the graph to extract the non-local self-similarity in the image. Second, GCESS uses spatial convolution and graph convolution to process the information in the image, so that local and non-local information can be effectively utilized. The network strengthens the non-local similarity between similar image patches while reconstructing images, making the reconstruction of structure more reliable. RESULTS: Experimental results on in vivo knee and brain data demonstrate that the proposed method achieves better artifact suppression and detail preservation than state-of-the-art methods, both visually and quantitatively. Under 1D Cartesian sampling with 4 × acceleration (AF = 4), the PSNR of knee data reached 34.19 dB, 1.05 dB higher than that of the compared methods; the SSIM achieved 0.8994, 2% higher than the compared methods. Similar results were obtained for the reconstructed images under other sampling templates as demonstrated in our experiment. CONCLUSIONS: The proposed method successfully constructs a hybrid graph convolution and spatial convolution network to reconstruct images. This method, through its training process, amplifies the non-local self-similarities, significantly benefiting the structural integrity of the reconstructed images. Experiments demonstrate that the proposed method outperforms the state-of-the-art reconstruction method in suppressing artifacts, as well as in preserving image details.

Agonistic analog of growth hormone-releasing hormone promotes neurofunctional recovery and neural regeneration in ischemic stroke.

Ischemic stroke can induce neurogenesis. However, most stroke-generated newborn neurons cannot survive. It has been shown that MR-409, a potent synthetic agonistic analog of growth hormone-releasing hormone (GHRH), can protect against some life-threatening pathological conditions by promoting cell proliferation and survival. The present study shows that long-term treatment with MR-409 (5 or 10 µg/mouse/d) by subcutaneous (s.c.) injection significantly reduces the mortality, ischemic insult, and hippocampal atrophy, and improves neurological functional recovery in mice operated on for transient middle cerebral artery occlusion (tMCAO). Besides, MR-409 can stimulate endogenous neurogenesis and improve the tMCAO-induced loss of neuroplasticity. MR-409 also enhances the proliferation and inhibits apoptosis of neural stem cells treated with oxygen and glucose deprivation-reperfusion. The neuroprotective effects of MR-409 are closely related to the activation of AKT/CREB and BDNF/TrkB pathways. In conclusion, the present study demonstrates that GHRH agonist MR-409 has remarkable neuroprotective effects through enhancing endogenous neurogenesis in cerebral ischemic mice.

Individuals with higher suicide risk showed more anger and disgust during rest.

Previous research showed that suicide risk was associated with the anger trait and the facial expression of anger when advising on life dilemmas. We investigated if suicide risk was associated with the facial expression of anger during rest, a state when individuals often reflect upon their lives. Participants took a 1-min rest before being assessed for suicide risk. We measured 147 participants' frontal-view facial expressions during their rest 1475-3694 times using automated facial expression analysis technology. Participants' suicide risk was significantly positively correlated with their anger and disgust during the rest, which may be related to psychological pain and death-related thoughts among individuals with suicide risk. Therefore, rest for clinical patients should not be seen simply as a "rest" for the mind. Rather, for counselors, rest may open a window to look into patients' inner thoughts that may be important to their lives.

Discriminating the Active Ru Species Towards the Selective Generation of Singlet Oxygen from Peroxymonosulfate: Nanoparticles Surpass Single-Atom Catalysts.

Singlet oxygen (1O2) is an exceptional reactive oxygen species in advanced oxidation processes for environmental remediation. Despite single-atom catalysts (SACs) representing the promising candidate for the selective generation of 1O2 from peroxymonosulfate (PMS), the necessity to meticulously regulate the coordination environment of metal centers poses a significant challenge in the precisely-controlled synthetic method. Another dilemma to SACs is their high surface free energy, which results in an inherent tendency for the surface migration and aggregation of metal atoms. We here for the first time reported that Ru nanoparticles (NPs) synthesized by the facile pyrolysis method behave as robust Fenton-like catalysts, outperforming Ru SACs, towards efficient activation of PMS to produce 1O2 with nearly 100 % selectivity, remarkably improving the degradation efficiency for target pollutants. Density functional theory calculations have unveiled that the boosted PMS activation can be attributed to two aspects: (i) enhanced adsorption of PMS molecules onto Ru NPs, and (ii) decreased energy barriers by offering adjacent sites for promoted dimerization of *O intermediates into adsorbed 1O2. This study deepens the current understanding of PMS chemistry, and sheds light on the design and optimization of Fenton-like catalysts.