Fluoride impairs vascular smooth muscle A7R5 cell lines via disrupting amino acids metabolism.

Given the insidious and high-fatality nature of cardiovascular diseases (CVDs), the emergence of fluoride as a newly identified risk factor demands serious consideration alongside traditional risk factors. While vascular smooth muscle cells (VSMCs) play a pivotal role in the progression of CVDs, the toxicological impact of fluoride on VSMCs remains largely uncharted. In this study, we constructed fluorosis model in SD rats and A7R5 aortic smooth muscle cell lines to confirm fluoride impaired VSMCs. Fluoride aggravated the pathological damage of rat aorta in vivo. Then A7R5 were exposed to fluoride with concentration ranging from 0 to 1200 µmol/L over a 24-h period, revealing a dose-dependent inhibition of cell proliferation and migration. The further metabolomic analysis showed alterations in metabolite profiles induced by fluoride exposure, notably decreasing organic acids and lipid molecules level. Additionally, gene network analysis underscored the frequency of fluoride's interference with amino acids metabolism, potentially impacting the tricarboxylic acid (TCA) cycle. Our results also highlighted the ATP-binding cassette (ABC) transporters pathway as a central element in VSMC impairment. Moreover, we observed a dose-dependent increase in osteopontin (OPN) and α-smooth muscle actin (α-SMA) mRNA level and a dose-dependent decrease in ABC subfamily C member 1 (ABCC1) and bestrophin 1 (BEST1) mRNA level. These findings advance our understanding of fluoride as a CVD risk factor and its influence on VSMCs and metabolic pathways, warranting further investigation into this emerging risk factor.

To Investigate the Mechanism of Qinpi Tongfeng Formula in Treating Acute Gouty Arthritis by UHPLC-Q-Orbitrap-MS, Network Pharmacology and Experimental Validation.

Background: Acute gouty arthritis (AGA) is characterized by the accumulation of monosodium urate crystals within the joints, leading to inflammation and severe pain. Western medicine treatments have limitations in addressing this condition. Previous studies have shown the efficacy of Qinpi Tongfeng formula (QPTFF) in treating AGA, but further investigation is needed to understand its mechanism of action. Methods: We used ultra-high-performance liquid chromatography tandem Q-Exactive Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap-MS) to identify compounds in QPTFF. Target proteins regulated by these compounds were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Chemistry Database, and Swiss Target Prediction Database. AGA-related targets were searched and screened from various databases, including Genecards, PharmGKB, Drugbank, etc. Intersection targets of QPTFF and AGA were analyzed for protein-protein interaction networks, GO function enrichment, and KEGG pathway enrichment. We then verified QPTFF's mechanism of action using an AGA rat model, assessing pathological changes via H&E staining and target expression via ELISA, RT-qPCR, and Western blot. Results: UHPLC-Q-Orbitrap-MS identified 207 compounds in QPTFF, with 55 selected through network pharmacology. Of 589 compound-regulated targets and 1204 AGA-related targets, 183 potential targets were implicated in QPTFF's treatment of AGA. Main target proteins included IL-1ß, NFKBIA, IL-6, TNF, CXCL8, and MMP9, with the IL-17 signaling pathway primarily regulated by QPTFF. Experimental results showed that medium and high doses of QPTFF significantly reduced serum inflammatory factors and MMP-9 expression, and inhibited IL-17A, IL-6, IKK-ß, and NF-κB p65 mRNA and protein expression in AGA rats compared to the model group. Conclusion: Key targets of QPTFF include IL-1ß, NFKBIA, IL-6, TNF-α, CXCL8, and MMP9. QPTFF effectively alleviates joint inflammation in AGA rats, with high doses demonstrating no liver or kidney toxicity. Its anti-inflammatory mechanism in treating AGA involves the IL-17A/NF-κB p65 signaling pathway.

Neuroprotective effects and mechanisms of action of artemisinin in retinal ganglion cells in a mouse model of traumatic optic neuropathy.

Introduction: Traumatic optic neuropathy is known to be a critical condition that can cause blindness; however, the specific mechanism underlying optic nerve injury is unclear. Recent studies have reported that artemisinin, considered vital in malaria treatment, can also be used to treat neurodegenerative diseases; however, its precise role and mechanism of action remain unknown. Therefore, in this study, we aimed to investigate the impact and probable mechanism of action of artemisinin in retinal ganglion cells (RGCs) in a mouse model of traumatic optic neuropathy induced by optic nerve crush (ONC). Methods: ONC was induced in the left eye of mice by short-term clamping of the optic nerve; oral artemisinin was administered daily. The neuroprotective effect of the drug was assessed using Tuj-1 staining in RGCs. In addition, the inflammatory response and the expression levels of phosphorylated tau protein and tau oligomers were observed using RT-qPCR, TUNEL assay, and fluorescence staining to investigate the underlying mechanisms. Results: Artemisinin increased the survival rate of RGCs 14 days after ONC. Artemisinin significantly reduced the levels of inflammatory factors such as CXCL10, CXCR3, and IL-1ß in the retina and decreased the apoptosis of RGCs. Moreover, downregulation of the phosphorylation of tau proteins and the expression of tau oligomers were observed after artemisinin treatment. Conclusion: Our results suggest that artemisinin can increase the survival rate of RGCs after ONC and reduce their apoptosis. This effect may be achieved by inhibiting the inflammatory response it triggers and downregulating tau protein phosphorylation and tau oligomer expression. These findings suggest the potential application of artemisinin as a therapeutic agent for neuropathy.

XAI Driven Intelligent IoMT Secure Data Management Framework.

The Internet of Medical Things (IoMT) has transformed traditional healthcare systems by enabling real-time monitoring, remote diagnostics, and data-driven treatment. However, security and privacy remain significant concerns for IoMT adoption due to the sensitive nature of medical data. Therefore, we propose an integrated framework leveraging blockchain and explainable artificial intelligence (XAI) to enable secure, intelligent, and transparent management of IoMT data. First, the traceability and tamper-proof of blockchain are used to realize the secure transaction of IoMT data, transforming the secure transaction of IoMT data into a two-stage Stackelberg game. The dual-chain architecture is used to ensure the security and privacy protection of the transaction. The main-chain manages regular IoMT data transactions, while the side-chain deals with data trading activities aimed at resale. Simultaneously, the perceptual hash technology is used to realize data rights confirmation, which maximally protects the rights and interests of each participant in the transaction. Subsequently, medical time-series data is modeled using bidirectional simple recurrent units to detect anomalies and cyberthreats accurately while overcoming vanishing gradients. Lastly, an adversarial sample generation method based on local interpretable model-agnostic explanations is provided to evaluate, secure, and improve the anomaly detection model, as well as to make it more explainable and resilient to possible adversarial attacks. Simulation results are provided to illustrate the high performance of the integrated secure data management framework leveraging blockchain and XAI, compared with the benchmarks.

Diagnostic efficiency of conventional ultrasound, shear wave elastography, and superb microvascular imaging in evaluating ulnar neuropathy at the elbow.

INTRODUCTION/AIMS: The current diagnosis of ulnar neuropathy at the elbow (UNE) relies mainly on the clinical presentation and nerve electrodiagnostic (EDX) testing, which can be uncomfortable and yield false negatives. The aim of this study was to investigate the diagnostic value of conventional ultrasound, shear wave elastography (SWE), and superb microvascular imaging (SMI) in diagnosing UNE. METHODS: We enrolled 40 patients (48 elbows) with UNE and 48 healthy volunteers (48 elbows). The patients were categorized as having mild, moderate or severe UNE based on the findings of EDX testing. The cross-sectional area (CSA) was measured using conventional ultrasound. Ulnar nerve (UN) shear wave velocity (SWV) and SMI were performed in a longitudinal plane. RESULTS: Based on the EDX findings, UNE severity was graded as mild in 4, moderate in 10, and severe in 34. The patient group showed increased ulnar nerve CSA and stiffness at the site of maximal enlargement (CSA mean at the site of max enlargement [CSAmax] and SWV mean at the site of max enlargement [SWVmax]), ulnar nerve CSA ratio, and stiffness ratio (elbow-to-upper arm), compared with the control group (p < .001). Furthermore, the severe UNE group showed higher ulnar nerve CSAmax and SWVmax compared with the mild and moderate UNE groups (p < .001). The cutoff values for diagnosis of UNE were 9.5 mm2 for CSAmax, 3.06 m/s for SWVmax, 2.00 for CSA ratio, 1.36 for stiffness ratio, and grade 1 for SMI. DISCUSSION: Our findings suggest that SWE and SMI are valuable diagnostic tools for the diagnosis and assessment of severity of UNE.

Extraction of genomic DNA for sequencing from snail Helix lucorum.

In the past, there were no easily distinct and recognizable features as a guide for precise clinical and genetic diagnosis of cases with chromosome microdeletions involving 15q26 including CHD2,. The present study analysed the clinical data and collected venous blood samples from a pediatric patient and his healthy family members for DNA testing. The whole-exome sequencing was performed by the next-generation sequencing (NGS). Chromosomal copy-number variations were tested based on NGS. We present a review of all cases with chromosome microdeletions affecting CHD2. A novel de novo 5.82-Mb deletion at 15q25.3-15q26.1 including CHD2 was identified in our patient who is an 11.6-year-old boy. We first found surprising efficacy of lamotrigine in controlling intractable drop seizures in the individual. These cases have development delay, behavioural problems, epilepsy, variable multiple anomalies, etc. Phenotypes of individuals with deletions involving 15q26 including CHD2 are highly variable with regard to facial features and multiple developmental anomalies. We first found the special clinical entity of development delay, behavioural problems, epilepsy, variable skeletal and muscular anomalies, abnormalities of variable multiple systems and characteristic craniofacial phenotypes in patients with chromosome microdeletions involving CHD2. The larger deletions involving 15q26 including CHD2 tend to cause the classical phenotype. A distinctive craniofacial appearance of the classical phenotype is midface hypoplasia and perifacial protrusion.

Neurotransmitters: Impressive regulators of tumor progression.

In contemporary times, tumors have emerged as the primary cause of mortality in the global population. Ongoing research has shed light on the significance of neurotransmitters in the regulation of tumors. It has been established that neurotransmitters play a pivotal role in tumor cell angiogenesis by triggering the transformation of stromal cells into tumor cells, modulating receptors on tumor stem cells, and even inducing immunosuppression. These actions ultimately foster the proliferation and metastasis of tumor cells. Several major neurotransmitters have been found to exert modulatory effects on tumor cells, including the ability to restrict emergency hematopoiesis and bind to receptors on the postsynaptic membrane, thereby inhibiting malignant progression. The abnormal secretion of neurotransmitters is closely associated with tumor progression, suggesting that focusing on neurotransmitters may yield unexpected breakthroughs in tumor therapy. This article presents an analysis and outlook on the potential of targeting neurotransmitters in tumor therapy.

DYNLL1 accelerates cell cycle via ILF2/CDK4 axis to promote hepatocellular carcinoma development and palbociclib sensitivity.

BACKGROUND: Disorder of cell cycle represents as a major driver of hepatocarcinogenesis and constitutes an attractive therapeutic target. However, identifying key genes that respond to cell cycle-dependent treatments still facing critical challenges in hepatocellular carcinoma (HCC). Increasing evidence indicates that dynein light chain 1 (DYNLL1) is closely related to cell cycle progression and plays a critical role in tumorigenesis. In this study, we explored the role of DYNLL1 in the regulation of cell cycle progression in HCC. METHODS: We analysed clinical specimens to assess the expression and predictive value of DYNLL1 in HCC. The oncogenic role of DYNLL1 was determined by gain or loss-of-function experiments in vitro, and xenograft tumour, liver orthotopic, and DEN/CCl4-induced mouse models in vivo. Mass spectrometry analysis, RNA sequencing, co-immunoprecipitation assays, and forward and reverse experiments were performed to clarify the mechanism by which DYNLL1 activates the interleukin-2 enhancer-binding factor 2 (ILF2)/CDK4 signalling axis. Finally, the sensitivity of HCC cells to palbociclib and sorafenib was assessed by apoptosis, cell counting kit-8, and colony formation assays in vitro, and xenograft tumour models and liver orthotopic models in vivo. RESULTS: DYNLL1 was significantly higher in HCC tissues than that in normal liver tissues and closely related to the clinicopathological features and prognosis of patients with HCC. Importantly, DYNLL1 was identified as a novel hepatocarcinogenesis gene from both in vitro and in vivo evidence. Mechanistically, DYNLL1 could interact with ILF2 and facilitate the expression of ILF2, then ILF2 could interact with CDK4 mRNA and delay its degradation, which in turn activates downstream G1/S cell cycle target genes CDK4. Furthermore, palbociclib, a selective CDK4/6 inhibitor, represents as a promising therapeutic strategy for DYNLL1-overexpressed HCC, alone or particularly in combination with sorafenib. CONCLUSIONS: Our work uncovers a novel function of DYNLL1 in orchestrating cell cycle to promote HCC development and suggests a potential synergy of CDK4/6 inhibitor and sorafenib for the treatment of HCC patients, especially those with increased DYNLL1.

5†kW power-level 1050†nm narrow-linewidth fiber amplifier enabled by biconical-tapered active fiber.

Effective wavelength extension is vital in the applications of high-power narrow-linewidth fiber lasers. In this work, we demonstrate a 5-kW power-level narrow-linewidth fiber amplifier at 1050 nm utilizing a homemade biconical-tapered Yb-doped fiber (BT-YDF). Up to ∼4.96 kW fiber laser is achieved with a 3 dB linewidth of ∼0.54 nm and a beam quality factor of Mx 2 = 1.46, My 2 = 1.6. The experimental comparisons reveal that BT-YDF has the advantages of improving a stimulated Raman scattering threshold and balancing transverse mode instability suppression in the fiber amplifier. This work could provide a good reference for extending the operating wavelength of high-power fiber amplifiers.

Picoliter Single-Cell Reactor for Proteome Profiling by In Situ Cell Lysis, Protein Immobilization, Digestion, and Droplet Transfer.

Global profiling of single-cell proteomes can reveal cellular heterogeneity, thus benefiting precision medicine. However, current mass spectrometry (MS)-based single-cell proteomic sample processing still faces technical challenges associated with processing efficiency and protein recovery. Herein, we present an innovative sample processing platform based on a picoliter single-cell reactor (picoSCR) for single-cell proteome profiling, which involves in situ protein immobilization and sample transfer. PicoSCR helped minimize surface adsorptive losses by downscaling the processing volume to 400 pL with a contact area of less than 0.4 mm2. Besides, picoSCR reached highly efficient cell lysis and digestion within 30 min, benefiting from optimal reagent and high reactant concentrations. Using the picoSCR-nanoLC-MS system, over 1400 proteins were identified from an individual HeLa cell using data-dependent acquisition mode. Proteins with copy number below 1000 were identified, demonstrating this system with a detection limit of 1.7 zmol. Furthermore, we profiled the proteome of circulating tumor cells (CTCs). Data are available via ProteomeXchange with the identifier PXD051468. Proteins associated with epithelial-mesenchymal transition and neutrophil extracellular traps formation (which are both related to tumor metastasis) were observed in all CTCs. The cellular heterogeneity was revealed by differences in signaling pathways within individual cells. These results highlighted the potential of the picoSCR platform to help discover new biomarkers and explore differences in biological processes between cells.

Encapsulation of Lactobacillus plantarum in W1/O/W2 double emulsions stabilized with the high-intensity ultrasound-treated pea protein and pectin.

This study focuses on developing a water-in-oil-in-water (W1/O/W2) double emulsion system using high-intensity ultrasound (HIU)-treated pea protein isolate (HIU-PPI) and pectin to encapsulate Lactobacillus plantarum (L. plantarum). The effects of ultrasound treatment on pea protein isolate (PPI) characteristics such as solubility, particle size, emulsification, surface hydrophobicity, and surface free sulfhydryl group were examined, determining optimal HIU processing conditions was 400 W for 10 min. The developed W1/O/W2 double emulsion system based on HIU-PPI demonstrated effective encapsulation and protection of L. plantarum, especially at the HIU-PPI concentration of 4 %, achieving an encapsulation efficiency of 52.65 %. Incorporating both HIU-PPI and pectin as emulsifiers increased the particle size and significantly enhanced the emulsion's viscosity. The highest bacterial encapsulation efficiency of the emulsion, 59.94 %, was attained at a HIU to pectin concentration ratio of 3:1. These emulsions effectively encapsulate and protect L. plantarum, with the concentration of HIU-PPI being a critical factor in enhancing probiotic survival under simulated gastrointestinal digestion. However, the concurrent utilization of pectin and HIU-PPI as emulsifiers did not provide a notable advantage compared to the exclusive use of HIU-PPI in enhancing probiotic viability during in vitro simulated digestion. This research offers valuable perspectives for the food industry on harnessing environmentally friendly, plant-based proteins as emulsifiers in probiotic delivery systems. It underscores the potential of HIU-modified pea protein and pectin in developing functional food products that promote the health benefits of probiotics.

Acoustic ejection tandem mass spectrometry for high-throughput screening of phencyclidine-type substances in urine, including authentic cases.

BACKGROUND: The abuse of the Phencyclidine-type substances, especially ketamine is a serious problem worldwide, and retrospective analysis are important for both the analysis and the identification of forms of drug abuse. The current major analytical methods, while all excellent in terms of accuracy, are time- and reagent-consuming. This depletion is made even more unfortunate by the fact that a large number of samples are negative in retrospective analyses. It is clear that a set of methods that can be analyzed both accurately and quickly need to be developed and applied to the screening and analysis of large quantities of samples. RESULTS: We described a urine test based on acoustic ejection mass spectrometry, which allows precise injection at very low volumes and near 1 ejection s-1 and data acquisition. The confidence in identification was increased by the characterization of the abundance ratio of the two pairs of ions. Urine samples could be diluted with water and loaded into a 384-well plate for sampling without complicated sample preparation. The sample in the transparent 384-well plate was pre-scanned by the laser, and then 20 nL droplets were ejected into the ion source for targeted analysis of 2 ion transitions per droplet totaling 9 targeted analytes in the sequence of acquisition methods. It took 90 min to screen 250 samples in this approach, yielding 10 ng mL-1 detection limits. Positive samples were further analyzed by UHPLC-MS/MS for confirmation and quantification of up to 36 analytes. SIGNIFICANCE: This was the first fast screening method for phencyclidine-type substances based on acoustic ejection mass spectrometry, which greatly reduces the analytical time, and can accomplish in 1.5 h what UHPLC-MS/MS needs 3 days to complete. And the samples can be analyzed without complicated sample preparation, and also can obtain good detectability. It was applied to a short-term retrospective analysis in Shanghai, and its accuracy was also extremely high.

Effect of cadmium on histopathological injuries and ultra-structural changes of kidney of the turtle Mauremys reevesii.

This research investigated the effect of cadmium on the tissue and cell of kidney of the turtle Mauremys reevesii. Twenty turtles were injected with cadmium at 0, 7.5, 15, 30 mg/kg separately and five turtles were taken in each group at two weeks after exposure. Kidneys were immediately excised and macroscopic pathological changes were observed, then the kidneys were fixed in 4% paraformaldehyde for histopathological examination and fixed in 2.5% (v/v) glutaraldehyde for examination of ultra-structure. The tissues of kidney presented varying degrees of histopathological lesions in cadmium treated turtles by a dose-dependent manner under the light microscope. Under transmission electron microscope, renal tubules cells presented varying degrees of dose-dependent lesions. The results indicated that cadmium can cause cell damages to the kidney, in particular to the mitochondria. Mitochondria can be used as one biomarker in the monitoring of cadmium pollution and its quantitative risk assessments.

Whole exome sequencing analyses reveal novel genes in telomere length and their biomedical implications.

Telomere length is a putative biomarker of aging and is associated with multiple age-related diseases. There are limited data on the landscape of rare genetic variations in telomere length. Here, we systematically characterize the rare variant associations with leukocyte telomere length (LTL) through exome-wide association study (ExWAS) among 390,231 individuals in the UK Biobank. We identified 18 robust rare-variant genes for LTL, most of which estimated effects on LTL were significant (> 0.2 standard deviation per allele). The biological functions of the rare-variant genes were associated with telomere maintenance and capping and several genes were specifically expressed in the testis. Three novel genes (ASXL1, CFAP58, and TET2) associated with LTL were identified. Phenotypic association analyses indicated significant associations of ASXL1 and TET2 with cancers, age-related diseases, blood assays, and cardiovascular traits. Survival analyses suggested that carriers of ASXL1 or TET2 variants were at increased risk for cancers; diseases of the circulatory, respiratory, and genitourinary systems; and all-cause and cause-specific deaths. The CFAP58 carriers were at elevated risk of deaths due to cancers. Collectively, the present whole exome sequencing study provides novel insights into the genetic landscape of LTL, identifying novel genes associated with LTL and their implications on human health and facilitating a better understanding of aging, thus pinpointing the genetic relevance of LTL with clonal hematopoiesis, biomedical traits, and health-related outcomes.

Effectiveness of integrated care for older adults-based interventions on depressive symptoms: A systematic review and meta-analysis.

AIM: To pool existing studies to assess the overall effectiveness of integrated care for older adults (ICOPE)-based interventions in improving depressive symptoms in older adults. DESIGN: A systematic review and meta-analysis. DATA SOURCES: Ten databases were systematically searched from inception to 15 July 2023 and the search was last updated on 2 September 2023. METHODS: Standardized mean difference (SMD) was calculated using random effects models. RoB 2 and GRADEpro GDT were used to assess the methodological quality and confidence in the cumulative evidence. Funnel plots, egger's test and begg's test were used to analyse publication bias. Sensitivity, subgroup and meta-regression analyses were performed to explore potential sources of heterogeneity. RESULTS: The results of 18 studies showed ICOPE-based interventions had a significant effect on improving depressive symptoms (SMD = -.84; 95% CI, -1.20 to -.3647; p < .001; 18 RCTs, 5010 participants; very low-quality evidence). Subgroup analysis showed the intervention group was characterized by mean age (70-80 years old), intervention duration between 6 to 12 months, gender (female <50%), non-frail older adults, depressed older adults and mixed integration appeared to be more effective. Sensitivity analysis found the results to be robust. CONCLUSION: ICOPE-based interventions may be a potentially effective alternative approach to reduce depressive symptoms in the older adults. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Healthcare professionals are expected to use ICOPE as one of the interventions for depressive symptoms in older adults, and this ICOPE could provide more comprehensive care services for older adults to reduce depressive symptoms. IMPACT: ICOPE-based interventions may be a potentially effective alternative approach to reduce depressive symptoms in the older adults. ICOPE-based interventions had a significant effect on reducing depressive symptoms in the older adults. The intervention group characterized by mean age of older adults, intervention duration, gender ratio, health condition and integration types may influence the effect size. REPORTING METHOD: According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution.

Wasserstein Discriminant Dictionary Learning for Graph Representation.

Mining discriminative graph topological information plays an important role in promoting graph representation ability. However, it suffers from two main issues: (1) the difficulty/complexity of computing global inter-class/intra-class scatters, commonly related to mean and covariance of graph samples, for discriminant learning; (2) the huge complexity and variety of graph topological structure that is rather challenging to robustly characterize. In this paper, we propose the Wasserstein Discriminant Dictionary Learning (WDDL) framework to achieve discriminant learning on graphs with robust graph topology modeling, and hence facilitate graph-based pattern analysis tasks. Considering the difficulty of calculating global inter-class/intra-class scatters, a reference set of graphs (aka graph dictionary) is first constructed by generating representative graph samples (aka graph keys) with expressive topological structure. Then, a Wasserstein Graph Representation (WGR) process is proposed to project input graphs into a succinct dictionary space through the graph dictionary lookup. To further achieve discriminant graph learning, a Wasserstein discriminant loss (WD-loss) is defined on the graph dictionary, in which the graph keys are optimizable, to make the intra-class keys more compact and inter-class keys more dispersed. Hence, the calculation of global Wasserstein metric (W-metric) centers can be bypassed. For sophisticated topology mining in the WGR process, a joint-Wasserstein graph embedding module is constructed to model both between-node and between-edge relationships across inputs and graph keys by encapsulating both the Wasserstein metric (between cross-graph nodes) and proposed novel Kron-Gromov-Wasserstein (KGW) metric (between cross-graph adjacencies). Specifically, the KGW-metric comprehensively characterizes the cross-graph connection patterns with the Kronecker operation, then adaptively captures those salient patterns through connection pooling. To evaluate the proposed framework, we study two graph-based pattern analysis problems, i.e. graph classification and cross-modal retrieval, with the graph dictionary flexibly adjusted to cater to these two tasks. Extensive experiments are conducted to comprehensively compare with existing advanced methods, as well as dissect the critical component of our proposed architecture. The experimental results validate the effectiveness of the WDDL framework.

A cross-scenario and cross-subject domain adaptation method for driving fatigue detection.

OBJECTIVE: The scarcity of electroencephalogram (EEG) data, coupled with individual and scenario variations, leads to considerable challenges in real-world EEG-based driver fatigue detection. We propose a domain adaptation method that utilizes EEG data collected from a laboratory to supplement real-world EEG data and constructs a cross-scenario and cross-subject driver fatigue detection model for real-world scenarios. Approach. First, we collect EEG data from subjects participating in a driving experiment conducted in both laboratory and real-world scenarios. To address the issue of data scarcity, we build a real-world fatigued driving detection model by integrating the real-world data with the laboratory data. Then, we propose a method named cross-scenario and cross-subject domain adaptation (CS2DA), which aims to eliminate the domain shift problem caused by individual variances and scenario differences. Adversarial learning is adopted to extract the common features observed across different subjects within the same scenario. The multikernel maximum mean discrepancy method is applied to further minimize scenario differences. Additionally, we propose a conditional multikernel maximum mean discrepancy constraint to better utilize label information. Finally, we use seven rules to fuse the predicted labels. Main results. We evaluate the CS2DA method through extensive experiments conducted on the two EEG datasets created in this work: the SEED-VLA and the SEED-VRW datasets. Different domain adaptation methods are used to construct a real-world fatigued driving detection model using data from laboratory and real-world scenarios, as well as a combination of both. Our findings show that the proposed CS2DA method outperforms the existing traditional and adversarial learning-based domain adaptation approaches. We also find that combining data from both laboratory and real-world scenarios improves the performance of the model. Significance. This study contributes two EEG-based fatigue driving datasets and demonstrates that the proposed CS2DA method can effectively enhance the performance of a real-world fatigued driving detection model.

Evaluating prognostic biomarkers for survival outcomes subject to informative censoring.

Prognostic biomarkers for survival outcomes are widely used in clinical research and practice. Such biomarkers are often evaluated using a C-index as well as quantities based on time-dependent receiver operating characteristic curves. Existing methods for their evaluation generally assume that censoring is uninformative in the sense that the censoring time is independent of the failure time with or without conditioning on the biomarker under evaluation. With focus on the C-index and the area under a particular receiver operating characteristic curve, we describe and compare three estimation methods that account for informative censoring based on observed baseline covariates. Two of them are straightforward extensions of existing plug-in and inverse probability weighting methods for uninformative censoring. By appealing to semiparametric theory, we also develop a doubly robust, locally efficient method that is more robust than the plug-in and inverse probability weighting methods and typically more efficient than the inverse probability weighting method. The methods are evaluated and compared in a simulation study, and applied to real data from studies of breast cancer and heart failure.

Visualizing Phase Evolution of Co2C for Efficient Fischer-Tropsch to Olefins.

Cobalt carbide (Co2C) possesses high catalytic efficiency Fischer-Tropsch synthesis (FTS) while the products selectivity appears sensitive to crystallography geometry. Since the Anderson-Schulz-Flory (ASF) distribution in FTS was broken through fabricating facetted Co2C nanocrystals, yet the underlying mechanism of Co2C crystallization remains unclarified suffering from sophisticated catalyst composition involving promoter agents. Herein, we report the synthesis of high-purity single-crystal nanoprisms (Co2C-p) for highly efficient FTS to lower olefins. Through comprehensive microstructure analysis, e.g. high-resolution TEM, in situ TEM and electron diffraction, as well as finite element simulation of gas flow field, for the first time we disclosed the full roadmap of forming catalytic active cobalt carbides, starting from reduction of Co3O4 precursor to CoO intermediate, then carburization into Co2C-s and subsequent ripening growth into Co2C-p. This gas-induced engineering of crystal phase provides a new synthesis strategy, with many new possibilities for precise design of metal-based catalyst for diverse catalytic applications. This article is protected by copyright. All rights reserved.

Terpene synthases GhTPS6 and GhTPS47 participate in resistance to Verticillium dahliae in upland cotton.

Terpene synthases (TPSs) are enzymes responsible for catalyzing the production of diverse terpenes, the largest class of secondary metabolites in plants. Here, we identified 107 TPS gene loci encompassing 92 full-length TPS genes in upland cotton (Gossypium hirsutum L.). Phylogenetic analysis showed they were divided into six subfamilies. Segmental duplication and tandem duplication events contributed greatly to the expansion of TPS gene family, particularly the TPS-a and TPS-b subfamilies. Expression profile analysis screened out that GhTPSs may mediate the interaction between cotton and Verticillium dahliae. Three-dimensional structures and subcellular localizations of the two selected GhTPSs, GhTPS6 and GhTPS47, which belong to the TPS-a subfamily, demonstrated similarity in protein structures and nucleus and cytoplasm localization. Virus-induced gene silencing (VIGS) of the two GhTPSs yielded plants characterized by increased wilting and chlorosis, more severe vascular browning, and higher disease index than control plants. Additionally, knockdown of GhTPS6 and GhTPS47 led to the down-regulation of cotton terpene synthesis following V. dahliae infection, indicating that these two genes may positively regulate resistance to V. dahliae through the modulation of disease-resistant terpene biosynthesis. Overall, our study represents a comprehensive analysis of the G. hirsutum TPS gene family, revealing their potential roles in defense responses against Verticillium wilt.