Scaling of the strange-metal scattering in unconventional superconductors.

Marked evolution of properties with minute changes in the doping level is a hallmark of the complex chemistry that governs copper oxide superconductivity as manifested in the celebrated superconducting domes and quantum criticality taking place at precise compositions1-4. The strange-metal state, in which the resistivity varies linearly with temperature, has emerged as a central feature in the normal state of copper oxide superconductors5-9. The ubiquity of this behaviour signals an intimate link between the scattering mechanism and superconductivity10-12. However, a clear quantitative picture of the correlation has been lacking. Here we report the observation of precise quantitative scaling laws among the superconducting transition temperature (Tc), the linear-in-T scattering coefficient (A1) and the doping level (x) in electron-doped copper oxide La2-xCexCuO4 (LCCO). High-resolution characterization of epitaxial composition-spread films, which encompass the entire overdoped range of LCCO, has enabled us to systematically map its structural and transport properties with unprecedented accuracy and with increments of Δx = 0.0015. We have uncovered the relations Tc ~ (xc - x)0.5 ~ (A1□)0.5, where xc is the critical doping in which superconductivity disappears and A1□ is the coefficient of the linear resistivity per CuO2 plane. The striking similarity of the Tc versus A1□ relation among copper oxides, iron-based and organic superconductors may be an indication of a common mechanism of the strange-metal behaviour and unconventional superconductivity in these systems.

CELLULOSE SYNTHASE-LIKE C proteins modulate cell wall establishment during ethylene-mediated root growth inhibition in rice.

The cell wall shapes plant cell morphogenesis and affects the plasticity of organ growth. However, the way in which cell wall establishment is regulated by ethylene remains largely elusive. Here, by analyzing cell wall patterns, cell wall composition and gene expression in rice (Oryza sativa, L.) roots, we found that ethylene induces cell wall thickening and the expression of cell wall synthesis-related genes, including CELLULOSE SYNTHASE-LIKE C1, 2, 7, 9, 10 (OsCSLC1, 2, 7, 9, 10) and CELLULOSE SYNTHASE A3, 4, 7, 9 (OsCESA3, 4, 7, 9). Overexpression and mutant analyses revealed that OsCSLC2 and its homologs function in ethylene-mediated induction of xyloglucan biosynthesis mainly in the cell wall of root epidermal cells. Moreover, OsCESA-catalyzed cellulose deposition in the cell wall was enhanced by ethylene. OsCSLC-mediated xyloglucan biosynthesis likely plays an important role in restricting cell wall extension and cell elongation during the ethylene response in rice roots. Genetically, OsCSLC2 acts downstream of ETHYLENE-INSENSITIVE3-LIKE1 (OsEIL1)-mediated ethylene signaling, and OsCSLC1, 2, 7, 9 are directly activated by OsEIL1. Furthermore, the auxin signaling pathway is synergistically involved in these regulatory processes. These findings link plant hormone signaling with cell wall establishment, broadening our understanding of root growth plasticity in rice and other crops.

CellSTAR: a comprehensive resource for single-cell transcriptomic annotation.

Large-scale studies of single-cell sequencing and biological experiments have successfully revealed expression patterns that distinguish different cell types in tissues, emphasizing the importance of studying cellular heterogeneity and accurately annotating cell types. Analysis of gene expression profiles in these experiments provides two essential types of data for cell type annotation: annotated references and canonical markers. In this study, the first comprehensive database of single-cell transcriptomic annotation resource (CellSTAR) was thus developed. It is unique in (a) offering the comprehensive expertly annotated reference data for annotating hundreds of cell types for the first time and (b) enabling the collective consideration of reference data and marker genes by incorporating tens of thousands of markers. Given its unique features, CellSTAR is expected to attract broad research interests from the technological innovations in single-cell transcriptomics, the studies of cellular heterogeneity & dynamics, and so on. It is now publicly accessible without any login requirement at: https://idrblab.org/cellstar.

TheMarker: a comprehensive database of therapeutic biomarkers.

Distinct from the traditional diagnostic/prognostic biomarker (adopted as the indicator of disease state/process), the therapeutic biomarker (ThMAR) has emerged to be very crucial in the clinical development and clinical practice of all therapies. There are five types of ThMAR that have been found to play indispensable roles in various stages of drug discovery, such as: Pharmacodynamic Biomarker essential for guaranteeing the pharmacological effects of a therapy, Safety Biomarker critical for assessing the extent or likelihood of therapy-induced toxicity, Monitoring Biomarker indispensable for guiding clinical management by serially measuring patients' status, Predictive Biomarker crucial for maximizing the clinical outcome of a therapy for specific individuals, and Surrogate Endpoint fundamental for accelerating the approval of a therapy. However, these data of ThMARs has not been comprehensively described by any of the existing databases. Herein, a database, named 'TheMarker', was therefore constructed to (a) systematically offer all five types of ThMAR used at different stages of drug development, (b) comprehensively describe ThMAR information for the largest number of drugs among available databases, (c) extensively cover the widest disease classes by not just focusing on anticancer therapies. These data in TheMarker are expected to have great implication and significant impact on drug discovery and clinical practice, and it is freely accessible without any login requirement at: https://idrblab.org/themarker.

International Union of Basic and Clinical Pharmacology CXIII: Nuclear Receptor Superfamily-Update 2023.

The NR superfamily comprises 48 transcription factors in humans that control a plethora of gene network programs involved in a wide range of physiologic processes. This review will summarize and discuss recent progress in NR biology and drug development derived from integrating various approaches, including biophysical techniques, structural studies, and translational investigation. We also highlight how defective NR signaling results in various diseases and disorders and how NRs can be targeted for therapeutic intervention via modulation via binding to synthetic lipophilic ligands. Furthermore, we also review recent studies that improved our understanding of NR structure and signaling. SIGNIFICANCE STATEMENT: Nuclear receptors (NRs) are ligand-regulated transcription factors that are critical regulators of myriad physiological processes. NRs serve as receptors for an array of drugs, and in this review, we provide an update on recent research into the roles of these drug targets.

Advances and opportunities in RNA structure experimental determination and computational modeling.

Beyond transferring genetic information, RNAs are molecules with diverse functions that include catalyzing biochemical reactions and regulating gene expression. Most of these activities depend on RNAs' specific structures. Therefore, accurately determining RNA structure is integral to advancing our understanding of RNA functions. Here, we summarize the state-of-the-art experimental and computational technologies developed to evaluate RNA secondary and tertiary structures. We also highlight how the rapid increase of experimental data facilitates the integrative modeling approaches for better resolving RNA structures. Finally, we provide our thoughts on the latest advances and challenges in RNA structure determination methods, as well as on future directions for both experimental approaches and artificial intelligence-based computational tools to model RNA structure. Ultimately, we hope the technological advances will deepen our understanding of RNA biology and facilitate RNA structure-based biomedical research such as designing specific RNA structures for therapeutics and deploying RNA-targeting small-molecule drugs.

Rice EIL1 interacts with OsIAAs to regulate auxin biosynthesis mediated by the tryptophan aminotransferase MHZ10/OsTAR2 during root ethylene responses.

Ethylene plays essential roles in adaptive growth of rice (Oryza sativa). Understanding of the crosstalk between ethylene and auxin (Aux) is limited in rice. Here, from an analysis of the root-specific ethylene-insensitive rice mutant mao hu zi 10 (mhz10), we identified the tryptophan aminotransferase (TAR) MHZ10/OsTAR2, which catalyzes the key step in indole-3-pyruvic acid-dependent Aux biosynthesis. Genetically, OsTAR2 acts downstream of ethylene signaling in root ethylene responses. ETHYLENE INSENSITIVE3 like1 (OsEIL1) directly activated OsTAR2 expression. Surprisingly, ethylene induction of OsTAR2 expression still required the Aux pathway. We also show that Os indole-3-acetic acid (IAA)1/9 and OsIAA21/31 physically interact with OsEIL1 and show promotive and repressive effects on OsEIL1-activated OsTAR2 promoter activity, respectively. These effects likely depend on their EAR motif-mediated histone acetylation/deacetylation modification. The special promoting activity of OsIAA1/9 on OsEIL1 may require both the EAR motifs and the flanking sequences for recruitment of histone acetyltransferase. The repressors OsIAA21/31 exhibit earlier degradation upon ethylene treatment than the activators OsIAA1/9 in a TIR1/AFB-dependent manner, allowing OsEIL1 activation by activators OsIAA1/9 for OsTAR2 expression and signal amplification. This study reveals a positive feedback regulation of ethylene signaling by Aux biosynthesis and highlights the crosstalk between ethylene and Aux pathways at a previously underappreciated level for root growth regulation in rice.

Gate-Controlled Neuromorphic Functional Transition in an Electrochemical Graphene Transistor.

Neuromorphic devices have attracted significant attention as potential building blocks for the next generation of computing technologies owing to their ability to emulate the functionalities of biological nervous systems. The essential components in artificial neural networks such as synapses and neurons are predominantly implemented by dedicated devices with specific functionalities. In this work, we present a gate-controlled transition of neuromorphic functions between artificial neurons and synapses in monolayer graphene transistors that can be employed as memtransistors or synaptic transistors as required. By harnessing the reliability of reversible electrochemical reactions between carbon atoms and hydrogen ions, we can effectively manipulate the electric conductivity of graphene transistors, resulting in a high on/off resistance ratio, a well-defined set/reset voltage, and a prolonged retention time. Overall, the on-demand switching of neuromorphic functions in a single graphene transistor provides a promising opportunity for developing adaptive neural networks for the upcoming era of artificial intelligence and machine learning.

Strategy for Identifying a Robust Metabolomic Signature Reveals the Altered Lipid Metabolism in Pituitary Adenoma.

Despite the well-established connection between systematic metabolic abnormalities and the pathophysiology of pituitary adenoma (PA), current metabolomic studies have reported an extremely limited number of metabolites associated with PA. Moreover, there was very little consistency in the identified metabolite signatures, resulting in a lack of robust metabolic biomarkers for the diagnosis and treatment of PA. Herein, we performed a global untargeted plasma metabolomic profiling on PA and identified a highly robust metabolomic signature based on a strategy. Specifically, this strategy is unique in (1) integrating repeated random sampling and a consensus evaluation-based feature selection algorithm and (2) evaluating the consistency of metabolomic signatures among different sample groups. This strategy demonstrated superior robustness and stronger discriminative ability compared with that of other feature selection methods including Student's t-test, partial least-squares-discriminant analysis, support vector machine recursive feature elimination, and random forest recursive feature elimination. More importantly, a highly robust metabolomic signature comprising 45 PA-specific differential metabolites was identified. Moreover, metabolite set enrichment analysis of these potential metabolic biomarkers revealed altered lipid metabolism in PA. In conclusion, our findings contribute to a better understanding of the metabolic changes in PA and may have implications for the development of diagnostic and therapeutic approaches targeting lipid metabolism in PA. We believe that the proposed strategy serves as a valuable tool for screening robust, discriminating metabolic features in the field of metabolomics.

Serum dithiothreitol-oxidizing capacity (DOC) is a promising biomarker for excluding significant liver fibrosis: a proof-of-concept study.

BACKGROUND: APRI and FIB-4 scores are used to exclude clinically significant fibrosis (defined as stage ≥ F2) in patients with chronic viral hepatitis. However, the cut-offs for these scores (generated by Youden indices) vary between different patient cohorts. This study aimed to evaluate whether serum dithiothreitol-oxidizing capacity (DOC), i.e., a surrogate test of quiescin sulfhydryl oxidase-1, which is a matrix remodeling enzyme, could be used to non-invasively identify significant fibrosis in patients with various chronic liver diseases (CLDs). METHODS: Diagnostic performance of DOC was compared with APRI and FIB-4 for identifying significant fibrosis. ROC curve analyses were undertaken in: a) two chronic hepatitis B (CHB) cohorts, independently established from hospitals in Wenzhou (n = 208) and Hefei (n = 120); b) a MASLD cohort from Wenzhou hospital (n = 122); and c) a cohort with multiple CLD etiologies (except CHB and MASLD; n = 102), which was identified from patients in both hospitals. Cut-offs were calculated using the Youden index. All CLD patients (n = 552) were then stratified by age for ROC curve analyses and cut-off calculations. RESULTS: Stratified by CLD etiology or age, ROC curve analyses consistently showed that the DOC test was superior to APRI and FIB-4 for discriminating between clinically significant fibrosis and no fibrosis, when APRI and FIB-4 showed poor/modest diagnostic performance (P < 0.05, P < 0.01 and P < 0.001 in 3, 1 and 3 cohort comparisons, respectively). Conversely, the DOC test was equivalent to APRI and FIB-4 when all tests showed moderate/adequate diagnostic performances (P > 0.05 in 11 cohort comparisons). DOC had a significant advantage over APRI or FIB-4 scores for establishing a uniform cut-off independently of age and CLD etiology (coefficients of variation of DOC, APRI and FIB-4 cut-offs were 1.7%, 22.9% and 47.6% in cohorts stratified by CLD etiology, 2.0%, 26.7% and 29.5% in cohorts stratified by age, respectively). The uniform cut-off was 2.13, yielded from all patients examined. Surprisingly, the uniform cut-off was the same as the DOC upper limit of normal with a specificity of 99%, estimated from 275 healthy control individuals. Hence, the uniform cut-off should possess a high negative predictive value for excluding significant fibrosis in primary care settings. A high DOC cut-off with 97.5% specificity could be used for detecting significant fibrosis (≥ F2) with an acceptable positive predictive value (87.1%). CONCLUSIONS: This proof-of-concept study suggests that the DOC test may efficiently rule out and rule in significant liver fibrosis, thereby reducing the numbers of unnecessary liver biopsies. Moreover, the DOC test may be helpful for clinicians to exclude significant liver fibrosis in the general population.

12-(S)-Hydroxyeicosatetraenoic Acid and GPR31 Signaling in Spinal Cord in Neuropathic Pain.

Neuropathic pain is a pressing unmet medical need requiring novel nonopioid-based therapeutic approaches. Using unbiased transcriptomic analysis, we found that the expression of Gpr31, a G protein-coupled receptor, increased in the dorsal horn of the spinal cord in rats with traumatic nerve injury-induced neuropathic pain. Daily intrathecal injections of siGpr31 reversed behavioral hypersensitivities in a time-dependent manner. GPR31, a Gα i protein-coupled receptor, has recently been cloned and is a receptor for 12-(S)-hydroxyeicosatetraenoic acid [12-(S)-HETE]. The lack of commercially available GPR31 antagonists has hampered the understanding of this receptor in pathophysiological states, including pain. To investigate this, our first approach was to identify novel GPR31 antagonists. Using a multidisciplinary approach, including in silico modeling, we identified the first highly potent and selective small-molecule GPR31 antagonist, SAH2. Here, we characterize the pharmacological activity in well-described models of neuropathic pain in rodents and provide evidence that 12-(S)-HETE/GPR31-dependent behavioral hypersensitivities are mediated through mitogen-activated protein kinase (MAPK) activation in the spinal cord. Our studies provide the pharmacological rationale for investigating contributions of GPR31 along the pain neuroaxis and the development of nonopioid GPR31-targeted strategies. SIGNIFICANCE STATEMENT: We have identified the first highly selective GPR31 antagonist. Using this antagonist, we have demonstrated that GPR31 signaling in the spinal cord is pronociceptive and MAPK pathways provided signaling mechanisms downstream of GPR31 activation in these processes.

An RRM domain protein SOE suppresses transgene silencing in rice.

Gene expression is regulated at multiple levels, including RNA processing and DNA methylation/demethylation. How these regulations are controlled remains unclear. Here, through analysis of a suppressor for the OsEIN2 over-expressor, we identified an RNA recognition motif protein SUPPRESSOR OF EIN2 (SOE). SOE is localized in nuclear speckles and interacts with several components of the spliceosome. We find SOE associates with hundreds of targets and directly binds to a DNA glycosylase gene DNG701 pre-mRNA for efficient splicing and stabilization, allowing for subsequent DNG701-mediated DNA demethylation of the transgene promoter for proper gene expression. The V81M substitution in the suppressor mutant protein mSOE impaired its protein stability and binding activity to DNG701 pre-mRNA, leading to transgene silencing. SOE mutation enhances grain size and yield. Haplotype analysis in c. 3000 rice accessions reveals that the haplotype 1 (Hap 1) promoter is associated with high 1000-grain weight, and most of the japonica accessions, but not indica ones, have the Hap 1 elite allele. Our study discovers a novel mechanism for the regulation of gene expression and provides an elite allele for the promotion of yield potentials in rice.

Deep-learning-assisted sidewall profiling white light interferometry system for accurately measuring 3D profiles and surface roughness on the groove sidewalls of precision components.

The accurate measurement of surface three-dimensional (3D) profile and roughness on the groove sidewalls of components is of great significance to diverse fields such as precision manufacturing, machining processes, energy transportation, medical equipment, and semiconductor industry. However, conventional optical measurement methods struggle to measure surface profiles on the sidewall of a small groove. Here, we present a deep-learning-assisted sidewall profiling white light interferometry system, which consists of a microprism-based interferometer, an optical path compensation device, and a convolutional neural network (CNN), for the accurate measurement of surface 3D profile and roughness on the sidewall of a small groove. We have demonstrated that the sidewall profiling white light interferometry system can achieve a measurement accuracy of 2.64 nm for the 3D profile on a groove sidewall. Moreover, we have demonstrated that the CNN-based single-image super-resolution (SISR) technique could improve the measurement accuracy of surface roughness by over 30%. Our system can be utilized in cases where the width of the groove is only 1 mm and beyond, limited only by the size of the microprism and the working distance of the objective used in our system.

Preparation of Medical 228Th-224Ra Radionuclide Generator Based on SiO2@TiO2 Microspheres.

224Ra (T1/2 = 3.63 d), an α-emitting radionuclide, holds significant promise in cancer endoradiotherapy. Current 224Ra-related therapy is still scarce because of the lack of reliable radionuclide supply. The 228Th-224Ra radionuclide generator can undoubtedly introduce continuous and sustainable availability of 224Ra for advanced nuclear medicine. However, conventional metal oxides for such radionuclide generators manifest suboptimal adsorption capacities for the parent nuclide, primarily attributable to their limited surface area. In this work, core-shell SiO2@TiO2 microspheres were proposed to develop as column materials for the construction of a 228Th-224Ra generator. SiO2@TiO2 microspheres were well prepared and systematically characterized, which has also been demonstrated to have good adsorption capacity to 228Th and very weak binding affinity toward 224Ra via simulated chemical separation. Upon introducing 228Th-containing solution onto the SiO2@TiO2 functional column, a 228Th-224Ra generator with excellent retention of the parent radionuclide and ideal elution efficiency of daughter radionuclide was obtained. The prepared 228Th-224Ra generator can produce 224Ra with high purity and medical usability in good elution efficiency (98.72%) even over five cycles. To the best of our knowledge, this is the first time that the core-shell mesoporous materials have been applied in a radionuclide generator, which can offer valuable insights for materials chemistry, radiochemical separation, and biological medicine.

Fetal overgrowth and weight trajectories during infancy and adiposity in early childhood.

BACKGROUND: Large-for-gestational age (LGA), a marker of fetal overgrowth, has been linked to obesity in adulthood. Little is known about how infancy growth trajectories affect adiposity in early childhood in LGA. METHODS: In the Shanghai Birth Cohort, we followed up 259 LGA (birth weight >90th percentile) and 1673 appropriate-for-gestational age (AGA, 10th-90th percentiles) children on body composition (by InBody 770) at age 4 years. Adiposity outcomes include body fat mass (BFM), percent body fat (PBF), body mass index (BMI), overweight/obesity, and high adiposity (PBF >85th percentile). RESULTS: Three weight growth trajectories (low, mid, and high) during infancy (0-2 years) were identified in AGA and LGA subjects separately. BFM, PBF and BMI were progressively higher from low- to mid-to high-growth trajectories in both AGA and LGA children. Compared to the mid-growth trajectory, the high-growth trajectory was associated with greater increases in BFM and the odds of overweight/obesity or high adiposity in LGA than in AGA children (tests for interactions, all P < 0.05). CONCLUSIONS: Weight trajectories during infancy affect adiposity in early childhood regardless of LGA or not. The study is the first to demonstrate that high-growth weight trajectory during infancy has a greater impact on adiposity in early childhood in LGA than in AGA subjects. IMPACT: Large-for-gestational age (LGA), a marker of fetal overgrowth, has been linked to obesity in adulthood, but little is known about how weight trajectories during infancy affect adiposity during early childhood in LGA subjects. The study is the first to demonstrate a greater impact of high-growth weight trajectory during infancy (0-2 years) on adiposity in early childhood (at age 4 years) in subjects with fetal overgrowth (LGA) than in those with normal birth size (appropriate-for-gestational age). Weight trajectory monitoring may be a valuable tool in identifying high-risk LGA children for close follow-ups and interventions to decrease the risk of obesity.

Ultra-high b-value DWI in rectal cancer: image quality assessment and regional lymph node prediction based on radiomics.

OBJECTIVES: This study aims to evaluate image quality and regional lymph node metastasis (LNM) in patients with rectal cancer (RC) on multi-b-value diffusion-weighted imaging (DWI). METHODS: This retrospective study included 199 patients with RC who had undergone multi-b-value DWI. Subjective (five-point Likert scale) and objective assessments of quality images were performed on DWIb1000, DWIb2000, and DWIb3000. Patients were randomly divided into a training (n = 140) or validation cohort (n = 59). Radiomics features were extracted within the whole volume tumor on ADC maps (b = 0, 1000 s/mm2), DWIb1000, DWIb2000, and DWIb3000, respectively. Five prediction models based on selected features were developed using logistic regression analysis. The performance of radiomics models was evaluated with a receiver operating characteristic curve, calibration, and decision curve analysis (DCA). RESULTS: The mean signal intensity of the tumor (SItumor), signal-to-noise ratio (SNR), and artifact and anatomic differentiability score gradually were decreased as the b-value increased. However, the contrast-to-noise (CNR) on DWIb2000 was superior to those of DWIb1000 and DWIb3000 (4.58 ± 0.86, 3.82 ± 0.77, 4.18 ± 0.84, p < 0.001, respectively). The overall image quality score of DWIb2000 was higher than that of DWIb3000 (p < 0.001) and showed no significant difference between DWIb1000 and DWIb2000 (p = 0.059). The area under curve (AUC) value of the radiomics model based on DWIb2000 (0.728) was higher than conventional ADC maps (0.690), DWIb1000 (0.699), and DWIb3000 (0.707), but inferior to multi-b-value DWI (0.739) in predicting LNM. CONCLUSION: DWIb2000 provides better lesion conspicuity and LNM prediction than DWIb1000 and DWIb3000 in RC. CLINICAL RELEVANCE STATEMENT: DWIb2000 offers satisfactory visualization of lesions. Radiomics features based on DWIb2000 can be applied for preoperatively predicting regional lymph node metastasis in rectal cancer, thereby benefiting the stratified treatment strategy. KEY POINTS: Lymph node staging is required to determine the best treatment plan for rectal cancer. DWIb2000 provides superior contrast-to-noise ratio and lesion conspicuity and its derived radiomics best predict lymph node metastasis. DWIb2000 may be recommended as the optimal b-value in rectal MRI protocol.

High expression of 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) associated with Diquat-induced damage.

Diquat (DQ) is a commonly used bipyridine herbicide known for its toxic properties and adverse effects on individuals. However, the mechanism underlying DQ-induced damage remain elusive. Our research aimed to uncover the regulatory network involved in DQ-induced damage. We analyzed publicly accessible gene expression patterns and performed research using a DQ-induced damage animal model. The GSE153959 dataset from the Gene Expression Omnibus collection and the animal model of DQ-induced kidney injury were used to identify differentially expressed genes (DEGs). Pathways including the regulation of DNA-templated transcription in response to stress, RNA polymerase II transcription regulator complex and transcription coregulatory activity were shown to be enriched in 21 DEGs. We used least absolute shrinkage and selection operator (LASSO) regression analysis to find possible diagnostic biomarkers for DQ-induced damage. Then, we used an HK-2 cell model to confirm these results. Additionally, we confirmed that 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) was the major gene associated with DQ-induced damage using multi-omics screening. The sample validation strongly suggested that HMGCS2 has promise as a diagnostic marker and may provide new targets for therapy in the context of DQ-induced damage.

Non-cytochrome P450 enzyme aldehyde oxidase is involved in the oxidative metabolic pathway of diquat and its detoxification effect.

Diquat (DQ) poisoning has garnered attention in recent years, primarily due to the rising incidence of cases worldwide, coupled with the absence of a viable antidote for its treatment. Despite the fact that diquat monopyridone (DQ-M) has been identified as a significant metabolite of DQ, the enzyme responsible for its formation remains unknown. In this study, we have identified aldehyde oxidase (AOX) as a vital enzyme involved in DQ oxidative metabolism. The metabolism of DQ to DQ-M was significantly inhibited by AOX inhibitors including raloxifene and hydralazine. The source of oxygen incorporated into DQ-M was proved to be from water through a H218O incubation experiment which further corroborated DQ-M formation via AOX metabolism. The product of DQ-M in vitro generated by fresh rat tissues co-incubation was consistent with its AOX expression. The result of the molecular docking analysis of DQ and AOX protein showed that DQ is capable of binding to AOX. Furthermore, the cytotoxicity of DQ was significantly higher than DQ-M at the same concentration tested in six cell types. This work is the first to uncover the involvement of aldehyde oxidase, a non-cytochrome P450 enzyme, in the oxidative metabolic pathway of diquat, thus providing a potential target for the development of detoxification treatment.

A national survey on current state and development needs of clinical and academic emergency medicine in China.

BACKGROUND: To characterize the current state of emergency medicine (EM) and the requirements for advancing EM clinical practice, education and research in China. METHODS: An anonymous electronic survey was conducted by Chinese Society of Emergency Medicine during September to October 2021. The survey contained 30 questions divided into 2 sections: the current state of EM development and the requirements for EM growth. RESULTS: 722 hospitals were included, of 487 were Level III and 235 were Level II hospitals. We found that after 40 years of development, EM had established a mature disciplinary system and refined sub-specialties including critical care, cardiopulmonary resuscitation, toxicology, disaster and emergency rescue. In Level III hospitals, 70.8% of EDs were standardized training centers for EM residents, but master's degree program, Doctor Degree program and post-doctoral degree program was approved in only 37.8%, 8.4% and 2.9% of EDs respectively and postgraduate curriculum was available in 1/4 of EDs. Only 8% have national or provincial key laboratories. In addition to advance clinical practice, there was also a high demand to improve teaching and research capacities, mainly focusing on literature review, research design and delivery, paper writing, residency training. CONCLUSIONS: EM has built a mature discipline system and refined sub-specialties in China. Teaching and research developed parallel with clinical practice. However, there was still a lack of EM master's and doctoral programs and research capacities need to be improved. More outstanding clinical and academic training should be provided to promote the rapid growth of EM in China.

HALNet: Partial Point Cloud Registration Based on Hybrid Attention and Deep Local Features.

Point cloud registration is an important task in computer vision and robotics which is widely used in 3D reconstruction, target recognition, and other fields. At present, many registration methods based on deep learning have better registration accuracy in complete point cloud registration, but partial registration accuracy is poor. Therefore, a partial point cloud registration network, HALNet, is proposed. Firstly, a feature extraction network consisting mainly of adaptive graph convolution (AGConv), two-dimensional convolution, and convolution block attention (CBAM) is used to learn the features of the initial point cloud. Then the overlapping estimation is used to remove the non-overlapping points of the two point clouds, and the hybrid attention mechanism composed of self-attention and cross-attention is used to fuse the geometric information of the two point clouds. Finally, the rigid transformation is obtained by using the fully connected layer. Five methods with excellent registration performance were selected for comparison. Compared with SCANet, which has the best registration performance among the five methods, the RMSE(R) and MAE(R) of HALNet are reduced by 10.67% and 12.05%. In addition, the results of the ablation experiment verify that the hybrid attention mechanism and fully connected layer are conducive to improving registration performance.