Quercetin induces ferroptosis by inactivating mTOR/S6KP70 pathway in oral squamous cell carcinoma.

Although recent studies increasingly suggest the potential anti-cancer effect of quercetin, the exact underlying mechanism remains poorly demonstrated in oral squamous cell carcinoma (oSCC). Therefore, our research explored the impacts of quercetin on the ferroptosis and mTOR/S6KP70 axis in oSCC cell lines. After treating oSCC cells with quercetin or indicated compounds and transfection with SLC7A11- or S6KP70-overexpressing plasmid, cell viability was detected by CCK-8 assay. The level of ferroptosis in oSCC cells was assessed by measuring ROS and GSH levels. The activation of mTOR/S6KP70 axis was assessed by Western blotting. Quercetin promoted ferroptosis in an mTOR/S6KP70-dependent manner to inhibit tumor growth in oSCC cells. Mechanistically, we revealed that quercetin induced lipid peroxidation and reduced GSH levels by repressing SLC7A11 expression in oSCC cells. Specifically, the effects of quercetin on ferroptosis and mTOR and S6KP70 phosphorylation were partially blocked by both mTOR agonist and S6KP70 overexpression. Moreover, mTOR inhibitor promoted ferroptosis in quercetin-treated oSCC cells. Our findings showed that ferroptosis may be a new anti-tumor mechanism of quercetin. Additionally, we identified that quercetin can target mTOR/S6KP70 cascade to inhibit the growth of oSCC cells.

Correction: Therapeutic effects of a walnut-derived peptide on NLRP3 inflammasome activation, synaptic plasticity, and cognitive dysfunction in T2DM mice.

Correction for 'Therapeutic effects of a walnut-derived peptide on NLRP3 inflammasome activation, synaptic plasticity, and cognitive dysfunction in T2DM mice' by Yanru Li et al., Food Funct., 2024, 15, 2295-2313, https://doi.org/10.1039/D3FO05076A.

A subject-specific unsupervised deep learning method for quantitative susceptibility mapping using implicit neural representation.

Quantitative susceptibility mapping (QSM) is an MRI-based technique that estimates the underlying tissue magnetic susceptibility based on phase signal. Deep learning (DL)-based methods have shown promise in handling the challenging ill-posed inverse problem for QSM reconstruction. However, they require extensive paired training data that are typically unavailable and suffer from generalization problems. Recent model-incorporated DL approaches also overlook the non-local effect of the tissue phase in applying the source-to-field forward model due to patch-based training constraint, resulting in a discrepancy between the prediction and measurement and subsequently suboptimal QSM reconstruction. This study proposes an unsupervised and subject-specific DL method for QSM reconstruction based on implicit neural representation (INR), referred to as INR-QSM. INR has emerged as a powerful framework for learning a high-quality continuous representation of the signal (image) by exploiting its internal information without training labels. In INR-QSM, the desired susceptibility map is represented as a continuous function of the spatial coordinates, parameterized by a fully-connected neural network. The weights are learned by minimizing a loss function that includes a data fidelity term incorporated by the physical model and regularization terms. Additionally, a novel phase compensation strategy is proposed for the first time to account for the non-local effect of tissue phase in data consistency calculation to make the physical model more accurate. Our experiments show that INR-QSM outperforms traditional established QSM reconstruction methods and the compared unsupervised DL method both qualitatively and quantitatively, and is competitive against supervised DL methods under data perturbations.

A combined in vitro and in silico study of the inhibitory mechanism of angiotensin-converting enzyme with peanut peptides.

Food-derived peptides with low molecular weight, high bioavailability, and good absorptivity have been exploited as angiotensin-converting enzyme (ACE) inhibitors. In the present study, in-vitro inhibition kinetics of peanut peptides, in silico screening, validation of ACE inhibitory activity, molecular dynamics (MD) simulations, and HUVEC cells were performed to systematically identify the inhibitory mechanism of ACE interacting with peanut peptides. The results indicate that FPHPP, FPHY, and FPHFD peptides have good thermal, pH, and digestive stability. MD trajectories elucidate the dynamic correlation between peptides and ACE and verify the specific binding interaction. Noteworthily, FPHPP is the best inhibitor with a strongest binding affinity and significantly increases NO, SOD production, and AT2R expression, and decreases ROS, MDA, ET-1 levels, ACE, and AT1R accumulation in Ang II-injury HUVEC cells.

Identification of idiopathic pulmonary fibrosis hub genes and exploration of the mechanisms of action of Jinshui Huanxian formula.

Idiopathic pulmonary fibrosis (IPF) is a common and heterogeneous chronic disease, and the mechanism of Jinshui Huanxian formula (JHF) on IPF remains unclear. For a total of 385 lung normal tissue samples from the Gene Expression Omnibus database, 37,777,639 gene pairs were identified through microarray and RNA-seq platforms. Using the individualized differentially expressed gene (DEG) analysis algorithm RankComp (FDR < 0.01), we identified 344 genes as DEGs in at least 95 % (n = 81) of the IPF samples. Of these genes, IGF1, IFNGR1, GLI2, HMGCR, DNM1, KIF4A, and TNFRSF11A were identified as hub genes. These genes were verified using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) in mice with pulmonary fibrosis (PF) and MRC-5 cells, and they were highly effective at classifying IPF samples in the independent dataset GSE134692 (AUC = 0.587-0.788) and mice with PF (AUC = 0.806-1.000). Moreover, JHF ameliorated the pathological changes in mice with PF and significantly reversed the changes in hub gene expression (KIF4A, IFNGR1, and HMGCR). In conclusion, a series of IPF hub genes was identified, and validated in an independent dataset, mice with PF, and MRC-5 cells. Moreover, the abnormal gene expression was normalized by JHF. These findings provide guidance for further exploration of the pathogenesis and treatment of IPF.

Effect of bi-enzyme hydrolysis on the properties and composition of hydrolysates of Manchurian walnut dreg protein.

Walnut dreg (WD) active peptides are an important source of dietary antioxidants; however, the products of conventional hydrolysis have limited industrial output owing to poor flavour and low bioactivity. To this end, in this study, we aimed to employ bvLAP, an aminopeptidase previously identified in our research, as well as commercially available Alcalase for bi-enzyme digestion. The flavour, antioxidant activity, and structures of products resulting from various digestion methods were compared. The results showed that the bi-enzyme digestion products had enhanced antioxidant activity, increased ß-sheet content, and reduced bitterness intensity from 9.65 to 6.93. Moreover, bi-enzyme hydrolysates showed a more diverse amino acid composition containing 1640 peptides with distinct sequences. These results demonstrate that bi-enzyme hydrolysis could be a potential process for converting WD into functional food ingredients. Additionally, our results provide new concepts that can be applied in waste processing and high-value utilisation of WD.

Therapeutic effects of a walnut-derived peptide on NLRP3 inflammasome activation, synaptic plasticity, and cognitive dysfunction in T2DM mice.

NLRP3 inflammasome activation plays a key role in the development of diabetes-induced cognitive impairment. However, strategies to inhibit NLRP3 inflammasome activation remain elusive. Herein, we evaluated the impact of a walnut-derived peptide, TWLPLPR (TW-7), on cognitive impairment in high-fat diet/streptozotocin-induced type 2 diabetes mellitus (T2DM) mice and explored its underlying mechanisms in high glucose-induced HT-22 cells. In the Morris water maze test, TW-7 alleviated cognitive deficits in mice; this was confirmed at the level of synaptic structure and dendritic spine density in the mouse hippocampus using transmission electron microscopy and Golgi staining. TW-7 increased the expression of synaptic plasticity-related proteins and suppressed the NEK7/NLRP3 inflammatory pathway, as determined by western blotting and immunofluorescence analysis. The mechanism of action of TW-7 was verified in an HT-22 cell model of high glucose-induced insulin resistance. Collectively, TW-7 could regulate T2DM neuroinflammation and synaptic function-induced cognitive impairment by inhibiting NLRP3 inflammasome activation and improving synaptic plasticity.

Any-nucleus distributed active programmable transmit coil.

PURPOSE: There are 118 known elements. Nearly all of them have NMR active isotopes and at least 39 different nuclei have biological relevance. Despite this, most of today's MRI is based on only one nucleus-1H. To facilitate imaging all potential nuclei, we present a single transmit coil able to excite arbitrary nuclei in human-scale MRI. THEORY AND METHODS: We present a completely new type of RF coil, the Any-nucleus Distributed Active Programmable Transmit Coil (ADAPT Coil), with fast switches integrated into the structure of the coil to allow it to operate at any relevant frequency. This coil eliminates the need for the expensive traditional RF amplifier by directly converting direct current (DC) power into RF magnetic fields with frequencies chosen by digital control signals sent to the switches. Semiconductor switch imperfections are overcome by segmenting the coil. RESULTS: Circuit simulations demonstrated the effectiveness of the ADAPT Coil approach, and a 9 cm diameter surface ADAPT Coil was implemented. Using the ADAPT Coil, 1H, 23Na, 2H, and 13C phantom images were acquired, and 1H and 23Na ex vivo images were acquired. To excite different nuclei, only digital control signals were changed, which can be programmed in real time. CONCLUSION: The ADAPT Coil presents a low-cost, scalable, and efficient method for exciting arbitrary nuclei in human-scale MRI. This coil concept provides further opportunities for scaling, programmability, lowering coil costs, lowering dead-time, streamlining multinuclear MRI workflows, and enabling the study of dozens of biologically relevant nuclei.

Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group.

This article provides recommendations for implementing QSM for clinical brain research. It is a consensus of the International Society of Magnetic Resonance in Medicine, Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available have generated a need in the neuroimaging community for guidelines on implementation. This article outlines considerations and implementation recommendations for QSM data acquisition, processing, analysis, and publication. We recommend that data be acquired using a monopolar 3D multi-echo gradient echo (GRE) sequence and that phase images be saved and exported in Digital Imaging and Communications in Medicine (DICOM) format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background field removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields within the brain mask should be removed using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of the whole brain as a region of interest in the analysis. The minimum acquisition and processing details required when reporting QSM results are also provided. These recommendations should facilitate clinical QSM research and promote harmonized data acquisition, analysis, and reporting.

Thrombospondin-1 promotes mechanical stress-mediated ligamentum flavum hypertrophy through the TGFß1/Smad3 signaling pathway.

Lumbar spinal canal stenosis is primarily caused by ligamentum flavum hypertrophy (LFH), which is a significant pathological factor. Nevertheless, the precise molecular basis for the development of LFH remains uncertain. The current investigation observed a notable increase in thrombospondin-1 (THBS1) expression in LFH through proteomics analysis and single-cell RNA-sequencing analysis of clinical ligamentum flavum specimens. In laboratory experiments, it was demonstrated that THBS1 triggered the activation of Smad3 signaling induced by transforming growth factor ß1 (TGFß1), leading to the subsequent enhancement of COL1A2 and α-SMA, which are fibrosis markers. Furthermore, experiments conducted on a bipedal standing mouse model revealed that THBS1 played a crucial role in the development of LFH. Sestrin2 (SESN2) acted as a stress-responsive protein that suppressed the expression of THBS1, thus averting the progression of fibrosis in ligamentum flavum (LF) cells. To summarize, these results indicate that mechanical overloading causes an increase in THBS1 production, which triggers the TGFß1/Smad3 signaling pathway and ultimately results in the development of LFH. Targeting the suppression of THBS1 expression may present a novel approach for the treatment of LFH.

Ten-year follow-up of very-high risk hypertensive patients undergoing renal sympathetic denervation.

OBJECTIVES: Renal denervation (RDN) has been proven to be effective in lowering blood pressure (BP) in patients, but previous studies have had short follow-ups and have not examined the effects of RDN on major cardiovascular outcomes. This study aimed to demonstrate the effectiveness and safety of RDN in the long-term treatment of hypertension and to determine if it has an effect on cardiovascular outcomes. METHODS: All patients with resistant hypertension who underwent RDN between 2011 and 2015 at Tianjin First Central Hospital were included in the study. Patients were followed up at 1,5 and 10 years and the longest follow-up was 12 years. Data were collected on office BP, home BP, ambulatory BP monitoring (ABPM), renal function, antihypertensive drug regimen, major adverse events (including acute myocardial infarction, stroke, cardiovascular death and all cause death) and safety events. RESULTS: A total of 60 participants with mean age 50.37 ±â€Š15.19 years (43.33% female individuals) completed long-term follow-up investigations with a mean of 10.02 ±â€Š1.72 years post-RDN. Baseline office SBP and DBP were 179.08 ±â€Š22.05 and 101.17 ±â€Š16.57 mmHg under a mean number of 4.22 ±â€Š1.09 defined daily doses (DDD), with a reduction of -35.93/-14.76 mmHg as compared with baseline estimates ( P  < 0.0001). Compared with baseline, ambulatory SBP and DBP after 10-years follow-up were reduced by 14.31 ±â€Š10.18 ( P  < 0.001) and 9 ±â€Š4.35 ( P  < 0.001) mmHg, respectively. In comparison to baseline, participants were taking fewer antihypertensive medications ( P  < 0.001), and their mean heart rate had decreased ( P  < 0.001). Changes in renal function, as assessed by estimated glomerular filtration rate (eGFR) and creatinine, were within the expected rate of age-related decline. No major adverse events related to the RDN procedure were observed in long-term consequences. All-cause mortality and cardiovascular mortality rates were 10 and 8.34%, respectively, for the 10-year period. CONCLUSION: The BP-lowering effect of RDN was safely sustained for at least 10 years post-procedure. More importantly, to the best of my knowledge, this is the first study to explore cardiovascular and all-cause mortality at 10 years after RDN.

Melatonin attenuates diabetic cardiomyopathy by increasing autophagy of cardiomyocytes via regulation of VEGF-B/GRP78/PERK signaling pathway.

AIMS: Diabetic cardiomyopathy (DCM) is a major cause of mortality in patients with diabetes, and the potential strategies for treating DCM are insufficient. Melatonin (Mel) has been shown to attenuate DCM, however, the underlying mechanism remains unclear. The role of vascular endothelial growth factor-B (VEGF-B) in DCM is little known. In present study, we aimed to investigate whether Mel alleviated DCM via regulation of VEGF-B and explored its underlying mechanisms. METHODS AND RESULTS: We found that Mel significantly alleviated cardiac dysfunction and improved autophagy of cardiomyocytes in type 1 diabetes mellitus (T1DM) induced cardiomyopathy mice. VEGF-B was highly expressed in DCM mice in comparison with normal mice, and its expression was markedly reduced after Mel treatment. Mel treatment diminished the interaction of VEGF-B and Glucose-regulated protein 78 (GRP78) and reduced the interaction of GRP78 and protein kinase RNA -like ER kinase (PERK). Furthermore, Mel increased phosphorylation of PERK and eIF2α, then up-regulated the expression of ATF4. VEGF-B-/- mice imitated the effect of Mel on wild type diabetic mice. Interestingly, injection with Recombinant adeno-associated virus serotype 9 (AAV9)-VEGF-B or administration of GSK2656157 (GSK), an inhibitor of phosphorylated PERK abolished the protective effect of Mel on DCM. Furthermore, rapamycin, an autophagy agonist displayed similar effect with Mel treatment; while 3-Methyladenine (3-MA), an autophagy inhibitor neutralized the effect of Mel on high glucose-treated neonatal rat ventricular myocytes. CONCLUSIONS: These results demonstrated that Mel attenuated DCM via increasing autophagy of cardiomyocytes, and this cardio-protective effect of Mel was dependent on VEGF-B/GRP78/PERK signaling pathway.

IMJENSE: Scan-Specific Implicit Representation for Joint Coil Sensitivity and Image Estimation in Parallel MRI.

Parallel imaging is a commonly used technique to accelerate magnetic resonance imaging (MRI) data acquisition. Mathematically, parallel MRI reconstruction can be formulated as an inverse problem relating the sparsely sampled k-space measurements to the desired MRI image. Despite the success of many existing reconstruction algorithms, it remains a challenge to reliably reconstruct a high-quality image from highly reduced k-space measurements. Recently, implicit neural representation has emerged as a powerful paradigm to exploit the internal information and the physics of partially acquired data to generate the desired object. In this study, we introduced IMJENSE, a scan-specific implicit neural representation-based method for improving parallel MRI reconstruction. Specifically, the underlying MRI image and coil sensitivities were modeled as continuous functions of spatial coordinates, parameterized by neural networks and polynomials, respectively. The weights in the networks and coefficients in the polynomials were simultaneously learned directly from sparsely acquired k-space measurements, without fully sampled ground truth data for training. Benefiting from the powerful continuous representation and joint estimation of the MRI image and coil sensitivities, IMJENSE outperforms conventional image or k-space domain reconstruction algorithms. With extremely limited calibration data, IMJENSE is more stable than supervised calibrationless and calibration-based deep-learning methods. Results show that IMJENSE robustly reconstructs the images acquired at 5× and 6× accelerations with only 4 or 8 calibration lines in 2D Cartesian acquisitions, corresponding to 22.0% and 19.5% undersampling rates. The high-quality results and scanning specificity make the proposed method hold the potential for further accelerating the data acquisition of parallel MRI.

Liver transplantation for pediatric patients with congenital heart disease: A single-center study in mainland China.

BACKGROUND: Liver transplantation (LT) is a serious cardiovascular stressor for patients with end-stage liver disease (ESLD). Data on the effects of cardiovascular diseases on pediatric LT is limited. No study on LT for pediatric patients with ESLD combined with congenital heart disease (CHD) has been reported from mainland China. METHODS: A total of 1005 patients were included in this study. The Kaplan-Meier method with log-rank testing was used to evaluate survival outcomes between groups. Univariable and multivariable Cox regression models were used to determine the risk factors for patient and graft survival. RESULTS: The most common indication for LT was biliary atresia (BA 90.3%). The prevalence of CHD was 3.8% (38). 42 CHD were found in 38 patients. The incidence of death and graft loss was more common in the CHD group than in the no-CHD group (13.2% vs. 5.0%, p = .045 and 15.8% vs. 6.2%, p = .019, respectively). The 5-year patient survival and graft survival in the CHD group versus the no-CHD group was 86.8% versus 94.7% (log-rank p = .022) and 84.2% versus 93.5% (log-rank p = .015), respectively. No significant differences were observed in re-transplantation, hepatic artery thrombosis (HAT), and portal vein thrombosis (PVT). After adjusting for age, BMI, etiology of LT, and other confounding factors, we can still find that the presence of CHD was associated with patient and graft survival after LT. CONCLUSION: The presence of CHD was associated with higher mortality and lower graft survival after LT. If possible, the cardiac defects should be addressed prior to LT.

Clinical report and genetic analysis of a Chinese patient with developmental and epileptic encephalopathy associated with novel biallelic variants in the ST3GAL3 gene.

BACKGROUND: Defects in the Golgi enzyme beta-galactoside-alpha-2,3-sialyltransferase-III (ST3Gal-III) caused by biallelic ST3GAL3 gene variants are associated with human neurodevelopmental disorders. Although ST3GAL3 gene variants have been linked to developmental and/or epileptic encephalopathy 15 (DEE15), their presence has only been reported in nine patients; however, the real frequency may be masked by insufficient screening. METHODS: Phenotypic information was collected from a male patient with severe psychomotor developmental delay and epileptic seizures, and genetic testing was done using whole exome sequencing. A molecular dynamics simulation analysis was performed to assess the potential impacts of the identified ST3GAL3 variants on the ST3Gal-III protein function, and a literature review was conducted to compare this case with previously described cases and assess disease manifestation and genetic characteristics. RESULTS: The patient inherited compound heterozygous ST3GAL3 gene variants, NM_006279.5:c.809G>A (p.Arg270Gln) and c.921dupG (p.Thr308fs*8). Neither variant had been previously reported in the general population. The p.Arg270Gln variant disrupted a hydrogen bond in the simulated ST3Gal-III protein structure. Among 25 patients with ST3GAL3 gene defects, eight ST3GAL3 gene variants were identified, and five variants had DEE signs. CONCLUSION: Patients with DEE15 may have novel ST3GAL3 gene variants, and this study may be the first clinical report of their occurrence in a Chinese patient. These variants should be considered when evaluating patients presenting with unexplained early-onset epileptic encephalopathy, severe developmental delay, and/or intellectual disability.

Copper-coordinated nanoassemblies based on photosensitizer-chemo prodrugs and checkpoint inhibitors for enhanced apoptosis-cuproptosis and immunotherapy.

Cuproptosis is a recently identified copper-dependent form of nonapoptotic cell death and holds great prospect in cancer treatment. One of the most intriguing aspects of cuproptosis is its ability to synergize with apoptosis-based cancer treatments. Herein, we presented a novel approach using copper-coordinated nanoassemblies (CCNAs) that were constructed by incorporating a photosensitizer Zinc Phthalocyanine (ZnPc)-chemotherapeutic (DOX) prodrug with a thioketal (TK) spacer and an IDO inhibitor (1-methyl tryptophan, 1-MT) as building blocks for Cu2+-coordination self-assembly to achieve combinational apoptosis-cuproptosis and immunotherapy. Upon NIR laser irradiation, the ZnPc component of CCNAs exhibited a photodynamic effect that generated reactive oxygen species (ROS). This triggered the release of DOX, leading to enhanced tumor cell apoptosis. Additionally, the presence of Cu2+ in the CCNAs not only enhanced the photodynamic process by catalyzing oxygen generation but also promoted the aggregation of toxic mitochondrial proteins, leading to cell cuproptosis. Importantly, the intensified cuproptosis-apoptosis effect triggered an immunogenic cell death (ICD) response. The released 1-MT complemented this response by reversing the immunosuppressive tumor microenvironment (ITM), synergistically amplifying anti-tumor immunity and suppressing the growth of primary and distant tumors. The findings of this study provide a new perspective on potential cancer treatments based on cuproptosis-apoptosis synergistic immunotherapy and stimulate further research in the design of advanced metal-coordinated nanomedicines. STATEMENT OF SIGNIFICANCE: The combination of cuproptosis and apoptosis that act with different mechanisms holds enormous potential in cancer treatment. Here, copper-coordinated nanoassemblies (CCNAs) based on photosensitizer-chemo prodrugs and checkpoint inhibitors were constructed for mediating cuproptosis-apoptosis and subsequently promoting cancer immunotherapy. CCNAs not only promoted the photodynamic effect and activation of chemotherapy through catalyzing the generation of oxygen but also induced toxic mitochondrial protein aggregation, leading to cell cuproptosis. These synergistic antitumor effects triggered robust immune responses with the aid of immune checkpoint blockade, almost eradicating primary tumors and inhibiting distant tumors by around 83 % without systemic toxicity.

BioTreasury: a community-based repository enabling indexing and rating of bioinformatics tools.

The exponential growth of bioinformatics tools in recent years has posed challenges for scientists in selecting the most suitable one for their data analysis assignments. Therefore, to aid scientists in making informed choices, a community-based platform that indexes and rates bioinformatics tools is urgently needed. In this study, we introduce BioTreasury ( http://biotreasury.rjmart.cn ), an integrated community-based repository that provides an interactive platform for users and developers to share their experiences in various bioinformatics tools. BioTreasury offers a comprehensive collection of well-indexed bioinformatics software, tools, and databases, totaling over 10,000 entries. In the past two years, we have continuously improved and maintained BioTreasury, adding several exciting features, including creating structured homepages for every tool and user, a hierarchical category of bioinformatics tools and classifying tools using large language model (LLM). BioTreasury streamlines the tool submission process with intelligent auto-completion. Additionally, BioTreasury provides a wide range of social features, for example, enabling users to participate in interactive discussions, rate tools, build and share tool collections for the public. We believe BioTreasury can be a valuable resource and knowledge-sharing platform for the biomedical community. It empowers researchers to effectively discover and evaluate bioinformatics tools, fostering collaboration and advancing bioinformatics research.

A chain mediation model of inclusive leadership and voice behavior among university teachers: evidence from China.

As a vital mode in which teachers can participate in university management, voice behavior is an important way of enhancing the efficiency of organizational decision-making, promoting democratic management, and facilitating sustainable development in universities. Although previous studies have confirmed the positive impact of inclusive leadership on employees' voice behavior, the mechanism underlying this effect remains unclear. Therefore, based on the cognitive-affective system theory of personality, this study aims to examine the mediating effects of psychological empowerment and organizational identification on the relationship between inclusive leadership and voice behavior among university teachers. A total of 517 valid questionnaires were administered to university teachers in mainland China using a convenience sampling approach. Structural equation modeling and bootstrap testing were used to analyze the data, and the results reveal that inclusive leadership is positively related to teachers' promotive and prohibitive voice behavior. This relationship is mediated by psychological empowerment and organizational identification, in which context a partial mediating effect is observed in the relationship between inclusive leadership and promotive voice and a full mediating effect is observed in the relationship between inclusive leadership and prohibitive voice. These findings can enrich the extant research on the impact of inclusive leadership in the field of higher education to a certain extent. Moreover, they provide a new perspective that can support an in-depth analysis of the mechanism underlying the effect of inclusive leadership and generate valuable practical insights into ways of stimulating voice behavior among university teachers.

Evaluation of deep learning-based feature selection for single-cell RNA sequencing data analysis.

BACKGROUND: Feature selection is an essential task in single-cell RNA-seq (scRNA-seq) data analysis and can be critical for gene dimension reduction and downstream analyses, such as gene marker identification and cell type classification. Most popular methods for feature selection from scRNA-seq data are based on the concept of differential distribution wherein a statistical model is used to detect changes in gene expression among cell types. Recent development of deep learning-based feature selection methods provides an alternative approach compared to traditional differential distribution-based methods in that the importance of a gene is determined by neural networks. RESULTS: In this work, we explore the utility of various deep learning-based feature selection methods for scRNA-seq data analysis. We sample from Tabula Muris and Tabula Sapiens atlases to create scRNA-seq datasets with a range of data properties and evaluate the performance of traditional and deep learning-based feature selection methods for cell type classification, feature selection reproducibility and diversity, and computational time. CONCLUSIONS: Our study provides a reference for future development and application of deep learning-based feature selection methods for single-cell omics data analyses.

The influence of challenge research stressors on research creativity among Chinese doctoral students: a mediated moderation model.

The research creativity of doctoral students is not solely fueled by their intrinsic motivation, but also thrives in an environment that offers challenging research opportunities, substantial support, and feedback from significant others. Based on the job demands-resources model, this study aims to explore the impact of challenge research stressors on the research creativity of Chinese doctoral students. A mediated moderation model was constructed to examine the mediating effect of achievement motivation and the moderating effect of supervisor developmental feedback on the relationship between challenge research stressors and research creativity. A total of 538 valid questionnaires were collected from doctoral students using convenience sampling and snowball sampling. The questionnaires included the Challenge Research Stressors Scale, the Research Creativity Scale, the Achievement Motivation Scale, and the Supervisor Developmental Feedback Scale. Regression analyses, bootstrap testing, and simple slope analyses were used to estimate the various relationships. The findings indicated that challenge research stressors had a positive effect on doctoral students' research creativity. Supervisor developmental feedback positively moderated the impact of challenge research stressors on the achievement motivation and research creativity of doctoral students. Achievement motivation partially mediated the influence of challenge research stressors on doctoral students' research creativity, and further fully mediated the interaction effect of challenge research stressors and supervisor developmental feedback on doctoral students' research creativity. These findings contribute not only to our understanding of the mechanisms and boundary conditions through which challenge research stressors impact the research creativity of doctoral students, but also provide valuable insights into how to stimulate and maintain their research creativity.