GPR55 activation improves anxiety- and depression-like behaviors of mice during methamphetamine withdrawal.

Methamphetamine is a potent and highly addictive neurotoxic psychostimulant that triggers a spectrum of adverse emotional responses during withdrawal. G-protein coupled receptor 55 (GPR55), a novel endocannabinoid receptor, is closely associated with mood regulation. Herein, we developed a murine model of methamphetamine-induced anxiety- and depressive-like behavior during abstinence which showed a decreased GPR55 expression in the hippocampus. Activation of GPR55 mitigated these behavioral symptoms, concomitantly ameliorating impairments in hippocampal neurogenesis and reducing neuroinflammation. These findings underscore the pivotal role of GPR55 in mediating the neuropsychological consequences of methamphetamine withdrawal, potentially via mechanisms involving the modulation of hippocampal neurogenesis and inflammation.

Scanning optoacoustic angiography for assessing structural and functional alterations in superficial vasculature of patients with post-thrombotic syndrome: A pilot study.

This study highlights the potential of scanning optoacoustic angiography (OA) in identifying alterations of superficial vasculature in patients with post-thrombotic syndrome (PTS) of the foot, a venous stress disorder associated with significant morbidity developing from long-term effects of deep venous thrombosis. The traditional angiography methods available in the clinics are not capable of reliably assessing the state of peripheral veins that provide blood outflow from the skin, a key hallmark of personalized risks of PTS formation after venous thrombosis. Our findings indicate that OA can detect an increase in blood volume, diameter, and tortuosity of superficial blood vessels. The inability to spatially separate vascular plexuses of the dermis and subcutaneous adipose tissue serves as a crucial criterion for distinguishing PTS from normal vasculature. Furthermore, our study demonstrates the ability of scanning optoacoustic angiography to detect blood filling decrease in an elevated limb position versus increase in a lowered position.

Integrated molybdenum single atom array sensors with multichannels for nitrite detection in foods.

Nitrite (NO2-) is present in a variety of foods, but the excessive intake of NO2- can indirectly lead to carcinogenic, teratogenic, mutagenicity and other risks to the human body. Therefore, the detection of NO2- is crucial for maintaining human health. In this study, an integrated array sensor for NO2- detection is developed based on molybdenum single atom material (IMSMo-SAC) using high-resolution electrohydrodynamic (EHD) printing technology. The sensor comprises three components: a printed electrode array, multichannels designed on polydimethylsiloxane (PDMS) and an electronic signal process device with bluetooth. By utilizing Mo-SAC to facilitate electron transfer during the redox reaction, rapid and efficient detection of NO2- can be achieved. The sensor has a wide linear range of 0.1 µM-107.8 mM, a low detection limit of 33 nM and a high sensitivity of 0.637 mA-1mM-1 cm-2. Furthermore, employing this portable array sensor allows simultaneously measurements of NO2- concentrations in six different foods samples with acceptable recovery rates. This array sensor holds great potential for detecting of small molecules in various fields.

Efficacy and safety of adjunctive perampanel treatment in pediatric patients with epilepsy aged 4-12 years: a real-world study.

OBJECTIVE: To determine the efficacy and safety of perampanel (PER) as an adjunctive therapy in children aged 4-12 years with epilepsy. METHODS: We performed a non-randomized, open-label, placebo-uncontrolled, real-world self-controlled study that included 216 young children (aged 4-12 years) with epilepsy who received PER as adjunctive therapy at the children's hospital affiliated with Chongqing Medical University from July 4, 2020, to September 20, 2023. RESULTS: (1) The efficacy rates of adjunctive PER therapy at 3, 6, 9, and 12 months were 62.8%, 67.8%, 65.3%, and 61.2%, respectively. PER showed efficacy in alleviating focal seizures, generalized tonic-clonic seizures, myoclonic seizures, and absence seizures. The efficacy rates for variants of self-limited epilepsy with centrotemporal spikes (SeLECTS) and Lennox-Gastaut syndrome (LGS) were 89.5% and 66.7%, respectively. (2) Focal non-motor onset seizures with or without impaired awareness, focal to bilateral tonic-clonic seizures (FBTCS), LGS, variants of SeLECTS, the number of concomitant antiseizure medications (ASMs), a family history of epilepsy, and focal lesions on cranial magnetic resonance imaging were independent factors affecting efficacy. The order of PER addition did not affect efficacy. The retention rates at 3, 6, 9, and 12 months were 90.7%, 84.7%, 74.7%, 64.9%, respectively. (3) Adverse reactions occurred in 45 patients (45/216, 20.8%), with irritability/aggressive behavior (18/216, 8.3%) and somnolence (14/216, 6.5%) being the most common. Twelve patients (12/216, 5.6%) withdrew from the study because of adverse reactions. CONCLUSION: In young Chinese children with epilepsy, PER is effective, safe, and well-tolerated as an adjunctive therapy, making it a viable option for use with broad-spectrum ASMs.

Assessing parameter efficient methods for pre-trained language model in annotating scRNA-seq data.

Annotating cell types of single-cell RNA sequencing (scRNA-seq) data is crucial for studying cellular heterogeneity in the tumor microenvironment. Recently, large-scale pre-trained language models (PLMs) have achieved significant progress in cell-type annotation of scRNA-seq data. This approach effectively addresses previous methods' shortcomings in performance and generalization. However, fine-tuning PLMs for different downstream tasks demands considerable computational resources, rendering it impractical. Hence, a new research branch introduces parameter-efficient fine-tuning (PEFT). This involves optimizing a few parameters while leaving the majority unchanged, leading to substantial reductions in computational expenses. Here, we utilize scBERT, a large-scale pre-trained model, to explore the capabilities of three PEFT methods in scRNA-seq cell type annotation. Extensive benchmark studies across several datasets demonstrate the superior applicability of PEFT methods. Furthermore, downstream analysis using models obtained through PEFT showcases their utility in novel cell type discovery and model interpretability for potential marker genes. Our findings underscore the considerable potential of PEFT in PLM-based cell type annotation, presenting novel perspectives for the analysis of scRNA-seq data.

Interfering with reconsolidation by rimonabant results in blockade of heroin-associated memory.

Drug-associated pathological memory remains a critical factor contributing to the persistence of substance use disorder. Pharmacological amnestic manipulation to interfere with drug memory reconsolidation has shown promise for the prevention of relapse. In a rat heroin self-administration model, we examined the impact of rimonabant, a selective cannabinoid receptor indirect agonist, on the reconsolidation process of heroin-associated memory. The study showed that immediately administering rimonabant after conditioned stimuli (CS) exposure reduced the cue- and herion + cue-induced heroin-seeking behavior. The inhibitory effects lasted for a minimum of 28 days. The effect of Rimonabant on reduced drug-seeking was not shown when treated without CS exposure or 6 hours after CS exposure. These results demonstrate a disruptive role of rimonabant on the reconsolidation of heroin-associated memory and the therapeutic potential in relapse control concerning substance use disorder.

Response of plants and soils to inundation duration and construction of the plant‒soil association mode in the hydro‒fluctuation belt of the reservoir wetland.

Hydro-Fluctuation Belt (HFB), a periodically exposed bank area formed by changes in water level fluctuations, is critical for damaging the reservoir wetland landscape and ecological balance. Thus, it is important to explore the mechanism of hydrological conditions on the plant-soil system of the HFB for protection of the reservoir wetland and landscape restoration. Here, we investigated the response of plant community characteristics and soil environment of the HFB of Tonghui River National Wetland Park (China), is a typical reservoir wetland, to the duration of inundation, as well as the correlation between the distribution of dominant plants and soil pH, nutrient contents, and enzyme activity by linear regression and canonical correlation analyses. The results show that as the duration of inundation decreases, the vegetation within the HFB is successional from annual or biennial herbs to perennial herbs and shrubs, with dominant plant species prominent and uneven distribution of species. Soil nutrient contents and enzyme activities of HFB decreased with increasing inundation duration. Dominant species of HFB plant community are related to soil environment, with water content, pH, urease, and available potassium being principle soil environmental factors affecting their distribution. When HFB was inundated for 0-30 days, soil pH was strongly acidic, with available potassium content above 150 mg kg-1 and higher urease activity, distributed with Arundo donax L., Polygonum perfoliatum L., Alternanthera philoxeroides (Mart.) Griseb., and Daucus carota L. communities. When inundated for 30-80 days, soil pH was acidic, with lower available potassium content (50-150 mg kg-1) and urease activity, distributed with Beckmannia syzigachne (Steud.) Fern.+ Polygonum lapathifolium L., Polygonum lapathifolium L., Medicago lupulina L. + Dysphania ambrosioides L. and Leptochloa panicea (Retz.) Ohwi communities. Using the constructed HFB plant-soil correlation model, changes in the wetland soil environment can be quickly judged by the succession of plant dominant species, which provides a simpler method for the monitoring of the soil environment in the reservoir wetland, and is of great significance for the scientific management and reasonable protection of the reservoir-type wetland ecosystem.

Enhanced Electrochemical CO2 Reduction to Formate over Phosphate-Modified In: Water Activation and Active Site Tuning.

Electrochemical CO2 reduction reaction (CO2RR) offers a sustainable strategy for producing fuels and chemicals. However, it suffers from sluggish CO2 activation and slow water dissociation. In this work, we construct a (P-O)δ- modified In catalyst that exhibits high activity and selectivity in electrochemical CO2 reduction to formate. A combination of in-situ characterizations and kinetic analyses indicate that (P-O)δ- has a strong interaction with K+(H2O)n, which effectively accelerates water dissociation to provide protons. In-situ attenuated total reflectance surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS) measurements together with density functional theory (DFT) calculations disclose that (P-O)δ- modification leads to a higher valence state of In active site, thus promoting CO2 activation and HCOO* formation, while inhibiting competitive hydrogen evolution reaction (HER). As a result, the (P-O)δ- modified oxide-derived In catalyst exhibits excellent formate selectivity across a broad potential window with a formate Faradaic efficiency as high as 92.1% at a partial current density of ~200 mA cm-2 and a cathodic potential of -1.2 V vs. RHE in an alkaline electrolyte.

Uncertain prediction of deformable image registration on lung CT using multi-category features and supervised learning.

The assessment of deformable registration uncertainty is an important task for the safety and reliability of registration methods in clinical applications. However, it is typically done by a manual and time-consuming procedure. We propose a novel automatic method to predict registration uncertainty based on multi-category features and supervised learning. Three types of features, including deformation field statistical features, deformation field physiologically realistic features, and image similarity features, are introduced and calculated to train the random forest regressor for local registration uncertain prediction. Deformation field statistical features represent the numerical stability of registration optimization, which are correlated to the uncertainty of deformation fields; deformation field physiologically realistic features represent the biomechanical properties of organ motions, which mathematically reflect the physiological reality of deformation; image similarity features reflect the similarity between the warped image and fixed image. The multi-category features comprehensively reflect the registration uncertainty. The strategy of spatial adaptive random perturbations is also introduced to accurately simulate spatial distribution of registration uncertainty, which makes deformation field statistical features more discriminative to the uncertainty of deformation fields. Experiments were conducted on three publicly available thoracic CT image datasets. Seventeen randomly selected image pairs are used to train the random forest model, and 9 image pairs are used to evaluate the prediction model. The quantitative experiments on lung CT images show that the proposed method outperforms the baseline method for uncertain prediction of classical iterative optimization-based registration and deep learning-based registration with different registration qualities. The proposed method achieves good performance for registration uncertain prediction, which has great potential in improving the accuracy of registration uncertain prediction.

Hydrolysis-dominated catalytic system: Hydrogen-free hydrogenolysis of lignin from Pd-MoOx/TiO2.

Lignin is continuously investigated by various techniques for valorization due to its high content of oxygen-containing functional groups. Catalytic systems employing hydrolysis­hydrogenolysis, leveraging the synergistic effect of redox metal sites and acid sites, exhibit efficient degradation of lignin. The predominance of either hydrolysis or hydrogenolysis reactions hinges upon the relative activity of acid and metal sites, as well as the intensity of the reductive atmosphere. In this study, the Pd-MoOx/TiO2 catalyst was found to primarily catalyze hydrolysis in the lignin depolymerization process, attributed to the abundance of moderate acidic sites on Pd and the redox-assisted catalysis of MoOx under inert conditions. After subjecting the reaction to 240 °C for 30 h, a yield of 48.22 wt% of total phenolic monomers, with 5.90 wt% consisting of diphenols, was achieved. Investigation into the conversion of 4-propylguaiacol (4-PG), a major depolymerized monomer of corncob lignin, revealed the production of ketone intermediates, a phenomenon closely linked to the unique properties of MoOx. Dehydrogenation of the propyl is a key step in initiating the reaction, and 4-PG could be almost completely transformed, accompanied by an over 97 % of 4-propylcatechol selectivity. This distinctive system lays a new theoretical groundwork for the eco-friendly valorization of lignin.

Genome-Wide Identification and Analysis of the EIN3/EIL Transcription Factor Gene Family in Doubled Haploid (DH) Poplar.

Ethylene (ET) is an important phytohormone that regulates plant growth, development and stress responses. The ethylene-insensitive3/ethylene-insensitive3-like (EIN3/EIL) transcription factor family, as a key regulator of the ET signal transduction pathway, plays an important role in regulating the expression of ET-responsive genes. Although studies of EIN3/EIL family members have been completed in many species, their role in doubled haploid (DH) poplar derived from another culture of diploid Populus simonii × P. nigra (donor tree, DT) remains ambiguous. In this study, a total of seven EIN3/EIL gene family members in the DH poplar genome were identified. Basic physical and chemical property analyses of these genes were performed, and these proteins were predicted to be localized to the nucleus. According to the phylogenetic relationship, EIN3/EIL genes were divided into two groups, and the genes in the same group had a similar gene structure and conserved motifs. The expression patterns of EIN3/EIL genes in the apical buds of different DH poplar plants were analyzed based on transcriptome data. At the same time, the expression patterns of PsnEIL1, PsnEIN3, PsnEIL4 and PsnEIL5 genes in different tissues of different DH plants were detected via RT-qPCR, including the apical buds, young leaves, functional leaves, xylem, cambium and roots. The findings presented above indicate notable variations in the expression levels of PsnEIL genes across various tissues of distinct DH plants. Finally, the PsnEIL1 gene was overexpressed in DT, and the transgenic plants showed a dwarf phenotype, indicating that the PsnEIL1 gene was involved in regulating the growth and development of poplar. In this study, the EIN3/EIL gene family of DH poplar was analyzed and functionally characterized, which provides a theoretical basis for the future exploration of the EIN3/EIL gene function.

Molecular tuning boosts asymmetric C-C coupling for CO conversion to acetate.

Electrochemical carbon dioxide/carbon monoxide reduction reaction offers a promising route to synthesize fuels and value-added chemicals, unfortunately their activities and selectivities remain unsatisfactory. Here, we present a general surface molecular tuning strategy by modifying Cu2O with a molecular pyridine-derivative. The surface modified Cu2O nanocubes by 4-mercaptopyridine display a high Faradaic efficiency of greater than 60% in electrochemical carbon monoxide reduction reaction to acetate with a current density as large as 380 mA/cm2 in a liquid electrolyte flow cell. In-situ attenuated total reflectance surface-enhanced infrared absorption spectroscopy reveals stronger *CO signal with bridge configuration and stronger *OCCHO signal over modified Cu2O nanocubes by 4-mercaptopyridine than unmodified Cu2O nanocubes during electrochemical CO reduction. Density function theory calculations disclose that local molecular tuning can effectively regulate the electronic structure of copper catalyst, enhancing *CO and *CHO intermediates adsorption by the stabilization effect through hydrogen bonding, which can greatly promote asymmetric *CO-*CHO coupling in electrochemical carbon monoxide reduction reaction.

Artificial-intelligence-based risk prediction and mechanism discovery for atrial fibrillation using heart beat-to-beat intervals.

BACKGROUND: Early diagnosis of atrial fibrillation (AF) is important for preventing stroke and other complications. Predicting AF risk in advance can improve early diagnostic efficiency. Deep learning has been used for disease risk prediction; however, it lacks adherence to evidence-based medicine standards. Identifying the underlying mechanisms behind disease risk prediction is important and required. METHODS: We developed an explainable deep learning model called HBBI-AI to predict AF risk using only heart beat-to-beat intervals (HBBIs) during sinus rhythm. We proposed a possible AF mechanism based on the model's explainability and verified this conjecture using confirmed AF risk factors while also examining new AF risk factors. Finally, we investigated the changes in clinicians' ability to predict AF risk using only HBBIs before and after learning the model's explainability. FINDINGS: HBBI-AI consistently performed well across large in-house and external public datasets. HBBIs with large changes or extreme stability were critical predictors for increased AF risk, and the underlying cause was autonomic imbalance. We verified various AF risk factors and discovered that autonomic imbalance was associated with all these factors. Finally, cardiologists effectively understood and learned from these findings to improve their abilities in AF risk prediction. CONCLUSIONS: HBBI-AI effectively predicted AF risk using only HBBI information through evaluating autonomic imbalance. Autonomic imbalance may play an important role in many risk factors of AF rather than in a limited number of risk factors. FUNDING: This study was supported in part by the National Key R&D Program and the National Natural Science Foundation of China.

Machine Learning-Assistant Colorimetric Sensor Arrays for Intelligent and Rapid Diagnosis of Urinary Tract Infection.

Urinary tract infections (UTIs), which can lead to pyelonephritis, urosepsis, and even death, are among the most prevalent infectious diseases worldwide, with a notable increase in treatment costs due to the emergence of drug-resistant pathogens. Current diagnostic strategies for UTIs, such as urine culture and flow cytometry, require time-consuming protocols and expensive equipment. We present here a machine learning-assisted colorimetric sensor array based on recognition of ligand-functionalized Fe single-atom nanozymes (SANs) for the identification of microorganisms at the order, genus, and species levels. Colorimetric sensor arrays are built from the SAN Fe1-NC functionalized with four types of recognition ligands, generating unique microbial identification fingerprints. By integrating the colorimetric sensor arrays with a trained computational classification model, the platform can identify more than 10 microorganisms in UTI urine samples within 1 h. Diagnostic accuracy of up to 97% was achieved in 60 UTI clinical samples, holding great potential for translation into clinical practice applications.

Targeted knockdown of PGAM5 in synovial macrophages efficiently alleviates osteoarthritis.

Osteoarthritis (OA) is a common degenerative disease worldwide and new therapeutics that target inflammation and the crosstalk between immunocytes and chondrocytes are being developed to prevent and treat OA. These attempts involve repolarizing pro-inflammatory M1 macrophages into the anti-inflammatory M2 phenotype in synovium. In this study, we found that phosphoglycerate mutase 5 (PGAM5) significantly increased in macrophages in OA synovium compared to controls based on histology of human samples and single-cell RNA sequencing results of mice models. To address the role of PGAM5 in macrophages in OA, we found conditional knockout of PGAM5 in macrophages greatly alleviated OA symptoms and promoted anabolic metabolism of chondrocytes in vitro and in vivo. Mechanistically, we found that PGAM5 enhanced M1 polarization via AKT-mTOR/p38/ERK pathways, whereas inhibited M2 polarization via STAT6-PPARγ pathway in murine bone marrow-derived macrophages. Furthermore, we found that PGAM5 directly dephosphorylated Dishevelled Segment Polarity Protein 2 (DVL2) which resulted in the inhibition of ß-catenin and repolarization of M2 macrophages into M1 macrophages. Conditional knockout of both PGAM5 and ß-catenin in macrophages significantly exacerbated osteoarthritis compared to PGAM5-deficient mice. Motivated by these findings, we successfully designed mannose modified fluoropolymers combined with siPGAM5 to inhibit PGAM5 specifically in synovial macrophages via intra-articular injection, which possessed desired targeting abilities of synovial macrophages and greatly attenuated murine osteoarthritis. Collectively, these findings defined a key role for PGAM5 in orchestrating macrophage polarization and provides insights into novel macrophage-targeted strategy for treating OA.

Experimental measurement of a multi-pole magnetorheological fluid clutch under air cooling.

Thermal characteristics have a profound effect on the allowable slip power and torque transmission stability of magnetorheological (MR) fluid devices. This paper investigates the thermal properties of a multi-pole MR clutch under different heat dissipation methods. First, the structure of the clutch is described, and heat generation and heat dissipation of the designed clutch are studied theoretically. Then, a numerical model is established, and several simulations are conducted on steady-state and transient temperatures under various operation conditions. After that, a temperature testing platform for the MR clutch is built, and several temperature experiments are carried out. The results show that the allowable steady-state slip power of the clutch under natural air cooling is about 147 W. Under forced air cooling, the allowable steady-state slip powers are 1.295, 1.555, and 1.790 kW, respectively, when the wind speeds are 3.5, 7.0, and 10.5 m/s. Furthermore, it turned out that the transmission torque of the MR clutch decreases with the increase in temperature. The experimental and simulated values of temperature are in good agreement in terms of numerical values and trends, indicating that the established temperature field simulation model can better reflect the temperature characteristics of the actual operation of the proposed multi-pole MR clutch. This research achievement can provide support for research on heat dissipation technology for MR devices with multiple excitation sources.

Accelerating the Phase Formation Kinetics of Alluaudite Sodium Iron Sulfate Cathodes via Ultrafast Thermal Shock.

Alluaudite sodium iron sulfate (NFS) exhibits great potential for use in sodium-ion battery cathodes due to its elevated operating potential and abundant element reserves. However, conventional solid-state methods demonstrate a low heating/cooling rate and sluggish reaction kinetics, requiring a long thermal treatment to effectively fabricate NFS cathodes. Herein, we propose a thermal shock (TS) strategy to synthesize alluaudite sodium iron sulfate cathodes using either hydrous or anhydrous raw materials. The analysis of the phase formation process reveals that TS treatment can significantly facilitate the removal of crystal water and decomposition of the intermediate phase Na2Fe(SO4)2 in the hydrous precursor. In the case of the anhydrous precursor, the kinetics of the combination reaction between Na2SO4 and FeSO4 can be also accelerated by TS treatment. Consequently, pure NFS phase formation can be completed after a substantially shorter time of post-sintering, thereby saving significant time and energy. The TS-treated NFS cathode derived from hydrous precursor exhibits higher retention after 200 cycles at 1C and better rate capability than the counterpart prepared by conventional long-term tube furnace sintering, demonstrating the great potential of this novel strategy.

Tobacco control knowledge and beliefs among healthcare workers in respiratory departments in Fujian Province, China: A cross-sectional study.

INTRODUCTION: Smoking prevalence is high in China, and healthcare workers are important for tobacco control. This study aimed to determine the smoking status, cognition of tobacco hazards, and smoking cessation-related knowledge among respiratory healthcare workers, and to explore their ability to provide smoking cessation assistance. METHODS: A cross-sectional study was conducted in 2021 among 1028 respiratory healthcare workers from 89 hospitals in Fujian Province, China. A self-designed electronic questionnaire was used to collect data on smoking status, knowledge of smoking hazards, and smoking cessation knowledge. Descriptive statistics were calculated for all questions. Logistic regression analysis was used to explore the relationship between awareness of the tobacco control goals of Healthy China 2030 and demographic characteristics. RESULTS: Among the healthcare workers surveyed, 3.4% were smokers, all of whom were male. Most respondents (99.4%) were aware of smoking as a cause of lung cancer, but awareness of smoking as a cause of non-respiratory cancer was lower. The awareness rate of smoking cessation support was high (>90%), but only 40.0% of participants were aware of the Healthy China 2030 tobacco control targets. Male (HR=2.16; 95% CI: 1.69-2.80) and participation in the cessation clinic (HR=1.47; 95% CI: 1.10-1.96) were associated with higher awareness of the targets. CONCLUSIONS: Respiratory healthcare workers in Fujian Province demonstrated a high level of awareness regarding behavioral and pharmacotherapy support for smoking cessation. In order to enable healthcare workers to play a more active role in tobacco control, there is a need to increase public awareness of smoking cessation services in Fujian Province.