Application of 5T glutamate chemical exchange saturation transfer imaging in brain tumors: preliminary results.

PURPOSE: Glutamate chemical exchange saturation transfer (GluCEST) is a non-invasive CEST imaging technique for detecting glutamate levels in tissues. We aimed to investigate the reproducibility of the 5T GluCEST technique in healthy volunteers and preliminarily explore its potential clinical application in patients with brain tumors. METHODS: Ten volunteers (4 males, mean age 29 years) underwent three 5T GluCEST imaging scans. The reproducibility of the three imaging GluCEST measurements was assessed using one-way repeated measures analysis of variance (ANOVA), generalized estimating equations, and linear mixed models. Twenty-eight patients with brain tumors (10 males, mean age 54 years) underwent a single GluCEST scan preoperatively, and t-tests were used to compare the differences in GluCEST values between different brain tumors. In addition, the diagnostic accuracy of GluCEST values in differentiating brain tumors was assessed using the receiver work characteristics (ROC) curve. RESULTS: The coefficients of variation of GluCEST values in healthy volunteers were less than 5% for intra-day, inter-day, and within-subjects and less than 10% for between-subjects. High-grade gliomas (HGG) had higher GluCEST values compared to low-grade gliomas (LGG) (P < 0.001). In addition, cerebellopontine angle (CPA) meningiomas had higher GluCEST values than acoustic neuromas (P < 0.001). The area under the curve (AUC) of the GluCEST value for differentiating CPA meningioma from acoustic neuroma was 0.93. CONCLUSION: 5T GluCEST images are highly reproducible in healthy brains. In addition, the 5T GluCEST technique has potential clinical applications in differentiating LGG from HGG and CPA meningiomas from acoustic neuromas.

Detection and identification of SARS-CoV-2 and influenza a based on microfluidic technology.

As of now, the global COVID-19 pandemic caused by SARS-CoV-2, which began in 2019, has been effectively controlled. However, the symptoms of influenza A virus infection were similar to those of SARS-CoV-2 infection, but they required different treatment approaches. To make the detection more accurate and the treatment more targeted. We developed a system that integrates RPA and CRISPR assays, allowing for the rapid, highly specific, and sensitive detection and differentiation of SARS-CoV-2, H1N1, and H3N2. Under isothermal amplification conditions, the RPA-CRISPR Cas12a detection system achieved a detection limit as low as 5 copies per µL, demonstrating excellent specificity. The measurement time was approximately 30 minutes. The RPA-CRISPR Cas12a detection system combined with the microfluidic chip we designed to simultaneously detect three viruses, providing a potential solution for efficient and reliable diagnosis.

A rapid simultaneous detection of duck hepatitis A virus 3 and novel duck reovirus based on RPA CRISPR Cas12a/Cas13a.

The mixed infection of duck hepatitis A virus 3 (DHAV-3) and novel duck reovirus (NDRV) has caused significant losses to the global duck farming industry. On-site point-of-care testing of viruses plays a crucial role in the early diagnosis, prevention, and disease control. Here, we proposed an RPA-CRISPR Cas12a/Cas13a one-pot strategy (DRCFS) for rapid and simultaneous detection of DHAV-3 and NDRV. This method integrated the reaction of RPA and CRISPR Cas12a/Cas13a in a single tube, eliminating the need to open the lid during the intermediate processes and thereby avoiding aerosol contamination. On this basis, we proposed a dual RPA-CRISPR strategy coupled with a lateral flow analysis platform (DRC-LFA). This circumvented the necessity for complex instruments, enabling direct visual interpretation of results, making the test more accessible and user-friendly. Our findings demonstrated that the DRCFS method could detect DHAV-3 and NDRV at concentrations as low as 100 copy/µL, while DRC-LFA achieved limit of 101 copies/µL within 35 min. Furthermore, when DRCFS, DRC-LFA, and qPCR were employed collectively for clinical samples analysis, all three methods yielded consistent results. The specificity, sensitivity, and user-friendly of these methods rendered them invaluable for on-site virus detection.

Comparative analysis for nutrients, flavor compounds, and lipidome revealed the edible value of pond-cultured male Pelodiscus sinensis with different ages.

Pelodiscus sinensis is an aquatic product with a long growth cycle in pond culture and high nutritional value meat. The flavor compounds, nutrients, and lipidome were investigated to explore the edible value changes of turtle meat aged 3 to 6 years (Y3 to Y6). Typically, P. sinensis meat is rich in high-quality protein (EAAI ≥81.22, AAS ≥86.47). Y6 has the highest level of Se, protein, amino acids, and high unsaturated fatty acids, including EPA + DHA. Y5 has the most delicious amino acids, polyunsaturated fatty acids, and key odorant content. The stronger flavor of Y5 may be mainly related to C18:2n6t and C18:2n6c. Further, triacylglycerols (TAG) and phosphatidylcholine (PC) were significant changes in Y5. Additionally, PI (16:0/18:1) was identified as the potential biomarker. These results provided available information on P. sinensis marketing age and revealed the potential impact of nutrients on the formation of VOCs.

The feasibility of half-dose contrast-enhanced scanning of brain tumours at 5.0 T: a preliminary study.

PURPOSE: This study investigated and compared the effects of Gd enhancement on brain tumours with a half-dose of contrast medium at 5.0 T and with a full dose at 3.0 T. METHODS: Twelve subjects diagnosed with brain tumours were included in this study and underwent MRI after contrast agent injection at 3.0 T (full dose) or 5.0 T (half dose) with a 3D T1-weighted gradient echo sequence. The postcontrast images were compared by two independent neuroradiologists in terms of the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and subjective image quality score on a ten-point Likert scale. Quantitative indices and subjective quality ratings were compared with paired Student's t tests, and interreader agreement was assessed with the intraclass correlation coefficient (ICC). RESULTS: A total of 16 enhanced tumour lesions were detected. The SNR was significantly greater at 5.0 T than at 3.0 T in grey matter, white matter and enhanced lesions (p < 0.001). The CNR was also significantly greater at 5.0 T than at 3.0 T for grey matter/tumour lesions, white matter/tumour lesions, and grey matter/white matter (p < 0.001). Subjective evaluation revealed that the internal structure and outline of the tumour lesions were more clearly displayed with a half-dose at 5.0 T (Likert scale 8.1 ± 0.3 at 3.0 T, 8.9 ± 0.3 at 5.0 T, p < 0.001), and the effects of enhancement in the lesions were comparable to those with a full dose at 3.0 T (7.8 ± 0.3 at 3.0 T, 8.7 ± 0.4 at 5.0 T, p < 0.001). All subjective scores were good to excellent at both 5.0 T and 3.0 T. CONCLUSION: Both quantitative and subjective evaluation parameters suggested that half-dose enhanced scanning via 5.0 T MRI might be feasible for meeting clinical diagnostic requirements, as the image quality remains optimal. Enhanced scanning at 5.0 T with a half-dose of contrast agents might benefit patients with conditions that require less intravenous contrast agent, such as renal dysfunction.

Bicomponent core/sheath melt-blown fibers for air filtration with ultra-low resistance.

With the escalating air pollution and frequent outbreaks of airborne diseases, there is a growing demand for personal protective filtration media. Melt-blown nonwovens have proven to be highly effective in capturing tiny particles, but their tightly packed fiber assemblages are more resistant to airflow and less comfortable to breathe. Here, we present a one-step melt-blown spinning process for the production of bicomponent core/sheath (BCS) crimped fibers and their application in high-efficiency, low-resistance air filtration. Fiber curl is caused by unbalanced internal stresses resulting from differences in the structure components, resulting in uneven shrinkage inside and outside the fibers. The resulting CM@S-2 filtration media features a uniform fiber curl and a porous fiber mesh structure, which reduces air filtration resistance. Under the same filtration conditions, the filtration efficiency of CM@S-2 (96.58% vs. 95.58%), filtration resistance (56.1 Pa vs. 108.0 Pa), quality factor (0.061 Pa-1vs. 0.029 Pa-1), and dust holding capacity (10.60 g m-2vs. 9.10 g m-2) were comparable to those of the single-component polypropylene filters. The filtration efficiency of the CM@S-2 remained above 94.0% after 30 days of indoor storage. Computational Fluid Dynamics (CFD) simulation demonstrated that crimped fibers effectively reduce pressure surges on the filter media caused by fiber accumulation. In comparative tests with commercial masks, the CM@S-2 cartridge masks demonstrated superior air permeability compared to commercial masks under similar filtration conditions. In conclusion, the bicomponent core/sheath melt-blown fibers significantly reduce air resistance and show excellent potential for application in protective masks.

On-site detection and differentiation of African swine fever virus variants using an orthogonal CRISPR-Cas12b/Cas13a-based assay.

The African swine fever virus (ASFV) and its variants have induced substantial economic losses in China, prompting a critical need for efficient detection methods. Several PCR-based methods have been developed to discriminate between wild-type ASFV and gene-deleted variants. However, the requirement for sophisticated equipment and skilled operators limits their use in field settings. Here, we developed a CRISPR-Cas12b/Cas13a-based detection assay that can identify ASFV variants with minimal equipment requirements and a short turnaround time. The assay utilizes the distinct DNA/RNA collateral cleavage preferences of Cas12b/Cas13a to detect two amplified targets from multiplex recombinase polymerase amplification (RPA) in a single tube, and the results can be visualized through fluorescent or lateral-flow readouts. When tested with clinical samples in field settings, our assay successfully detected all ASFV-positive samples in less than 60 min. This assay provides a rapid on-site surveillance tool for detecting ASFV and its emerging variants.

Association of ADAMTS13 activity with cerebral deep medullary vein: A community-based cross-sectional study.

Objectives: This study aims to investigate whether circulating ADAMTS13 activity can offer insights into the mechanism of pathophysiological changes in deep medullary veins (DMVs). Methods: This study was conducted on a community cohort of elderly individuals in Shanghai. Plasma von Willebrand factor (VWF) levels and ADAMTS13 activity were measured. A validated DMV score described the overall burden of DMV on the brain. Through ordinal regression models, we investigated the correlation between VWF levels, ADAMTS13 activity, and increasing severity of DMV score while adjusting for demographics and cardiovascular risk factors. Results: The study enrolled 262 subjects according to the inclusion criteria. The mean VWF level (1.35 ± 0.25) was higher in the DMV group than in the group without DMV (1.25 ± 0.30) (p = 0.025), and ADAMTS13 activity (83.76 ± 7.96) was relatively lower. After adjusting for age, sex, alcohol consumption, smoking, hypertension, and diabetes, reduced ADAMTS13 activity [ß = -7.78; 95 % CI (-10.21, -5.35) p < 0.01] was associated with DMV. Moreover, correlation analysis indicated that ADAMTS13 activity was negatively correlated with the DMV score (Kendall's tau-b = -0.53, p < 0.001). Discussion: In summary, there was an inverse correlation observed between ADAMTS13 activity and the DMV score, which may provide some clinical clues for exploring the potential pathogenesis of DMV.

Quantifying H&E staining results, grading and predicting IDH mutation status of gliomas using hybrid multi-dimensional MRI.

OBJECTIVE: To assess the performance of hybrid multi-dimensional magnetic resonance imaging (HM-MRI) in quantifying hematoxylin and eosin (H&E) staining results, grading and predicting isocitrate dehydrogenase (IDH) mutation status of gliomas. MATERIALS AND METHODS: Included were 71 glioma patients (mean age, 50.17 ± 13.38 years; 35 men). HM-MRI images were collected at five different echo times (80-200 ms) with seven b-values (0-3000 s/mm2). A modified three-compartment model with very-slow, slow and fast diffusion components was applied to calculate HM-MRI metrics, including fractions, diffusion coefficients and T2 values of each component. Pearson correlation analysis was performed between HM-MRI derived fractions and H&E staining derived percentages. HM-MRI metrics were compared between high-grade and low-grade gliomas, and between IDH-wild and IDH-mutant gliomas. Using receiver operational characteristic (ROC) analysis, the diagnostic performance of HM-MRI in grading and genotyping was compared with mono-exponential models. RESULTS: HM-MRI metrics FDvery-slow and FDslow demonstrated a significant correlation with the H&E staining results (p < .05). Besides, FDvery-slow showed the highest area under ROC curve (AUC = 0.854) for grading, while Dslow showed the highest AUC (0.845) for genotyping. Furthermore, a combination of HM-MRI metrics FDvery-slow and T2Dslow improved the diagnostic performance for grading (AUC = 0.876). DISCUSSION: HM-MRI can aid in non-invasive diagnosis of gliomas.

Raman lidar at 355 nm using low dead time photon counting for atmospheric aerosol measurements.

Photon counting is an effective way to enhance the dynamic range of the data acquisition system (DAQ) in Raman lidars. However, there exists a deficiency of relatively high dead times among current options, which necessitates an additional calibration procedure for the nonlinearity of the photon counting signal, thus leading to unanticipated errors. A field programmable gate array (FPGA)-based photon counting module has been proposed and implemented in a Raman lidar, offering two operational channels. Through observational experiments, it was determined that this module has an overall dead time of 1.13 ns taking advantage of the high-speed amplifier/discriminator pair and the logic design, a significant improvement compared to the 4.35 ns of a commercially used Licel transient recorder within the same counting rate range. This notably low dead time implies that its output maintains sufficient linearity even at substantially high counting rates. As a result, the need for a dead time calibration procedure prior to signal integration with the analog signal is eliminated, reducing uncertainty in the final integrated signal, and even in the retrieval result. The backscattering result of the comparison between this module and a transient recorder indicates that a more precise performance can be acquired benefiting from this hardware upgrading.

Metabolism/Immunity Dual-Regulation Thermogels Potentiating Immunotherapy of Glioblastoma Through Lactate-Excretion Inhibition and PD-1/PD-L1 Blockade.

Intrinsic immunosuppressive tumor microenvironment (ITM) and insufficient tumor infiltration of T cells severely impede the progress of glioblastoma (GBM) immunotherapy. In this study, it is identify that inhibiting the expression of glucose transporter 1 (GLUT1) can facilitate the prevention of lactate excretion from tumor glycolysis, which significantly alleviates the lactate-driven ITM by reducing immunosuppressive tumor-associated macrophages (TAMs) and regulatory T cells (Tregs). Simultaneously, the findings show that the generated inflammatory cytokine IFN-γ during immune activation aggravates the immune escape by upregulating immune checkpoint programmed death-ligand 1 (PD-L1) in tumor cells and TAMs. Therefore, an injectable thermogel loaded with a GLUT1 inhibitor BAY-876 and a PD-1/PD-L1 blocker BMS-1 (Gel@B-B) for dual-regulation of metabolism and immunity of GBM is developed. Consequently, in situ injection of Gel@B-B significantly delays tumor growth and prolongs the survival of the orthotopic GBM mouse model. By actively exposing tumor antigens to antigen-presenting cells, the GBM vaccine combined with Gel@B-B is found to significantly increase the fraction of effector T cells (Th1/CTLs) in the tumor microenvironment, thereby remarkably mitigating tumor recurrence long-term. This study may provide a promising strategy for GBM immunotherapy.

Improved Detection of Target Metabolites in Brain Tumors with Intermediate TE, High SNR, and High Bandwidth Spin-Echo Sequence at 5T.

BACKGROUND AND PURPOSE: Due to high chemical shift displacement, challenges emerge at ultra-high fields when measuring metabolites using 1H-MRS. Our goal was to investigate how well the high SNR and high bandwidth spin-echo (HISE) technique perform at 5T for detecting target metabolites in brain tumors. MATERIALS AND METHODS: Twenty-six subjects suspected of having brain tumors were enrolled. HISE and point-resolved spectroscopy (PRESS) single-voxel spectroscopy scans were collected with a 5T clinical scanner with an intermediate TE (TE = 144 ms). The main metabolites, including total NAA, Cr, and total Cho, were accessed and compared between HISE and PRESS using a paired Student t test, with full width at half maximum and SNR as covariates. The detection rate of specific metabolites, including lactate, alanine, and lipid, and subjective spectral quality were accessed and compared between HISE and PRESS. RESULTS: Twenty-three pathologically confirmed brain tumors were included. Only the full width at half maximum for total NAA was significantly lower with HISE than with PRESS (P < .05). HISE showed a significantly higher SNR for total NAA, Cr, and total Cho compared with PRESS (P < .05). Lactate was detected in 21 of the 23 cases using HISE, but in only 4 cases using PRESS. HISE detected alanine in 8 of 9 meningiomas, whereas PRESS detected alanine in just 3 meningiomas. PRESS found lipid in more cases than HISE, while HISE outperformed PRESS in terms of subjective spectral quality. CONCLUSIONS: HISE outperformed the clinical standard PRESS technique in detecting target metabolites of brain tumors at 5T, particularly lactate and alanine.

B cell activation and autoantibody production in autoimmune diseases.

B cells are central players in the immune system, responsible for producing antibodies and modulating immune responses. This review explores the intricate relationship between aberrant B cell activation and the development of autoimmune diseases, emphasizing the essential role of B cells in these conditions. We also summarize B cell receptor signaling and Toll-like receptor signaling in B cell activation, as well as their association with autoimmune diseases, shedding light on the molecular mechanisms behind these associations. Additionally, we explore the clinical observations involving B cell activation and their significance in autoimmune disease management. Various clinical studies related to B cell-targeted therapies are also discussed, offering insights into potential avenues for improving treatment strategies. Overall, this review serves as a resource for researchers and clinicians in the field of immunology and autoimmune diseases, providing a general view of B cell signaling and its role in autoimmunity.

Ion channel TRPV2 is critical in enhancing B cell activation and function.

The function of transient receptor potential vanilloid (TRPV) cation channels governing B cell activation remains to be explored. We present evidence that TRPV2 is highly expressed in B cells and plays a crucial role in the formation of the B cell immunological synapse and B cell activation. Physiologically, TRPV2 expression level is positively correlated to influenza-specific antibody production and is low in newborns and seniors. Pathologically, a positive correlation is established between TRPV2 expression and the clinical manifestations of systemic lupus erythematosus (SLE) in adult and child SLE patients. Correspondingly, mice with deficient TRPV2 in B cells display impaired antibody responses following immunization. Mechanistically, the pore and N-terminal domains of TRPV2 are crucial for gating cation permeation and executing mechanosensation in B cells upon antigen stimulation. These processes synergistically contribute to membrane potential depolarization and cytoskeleton remodeling within the B cell immunological synapse, fostering efficient B cell activation. Thus, TRPV2 is critical in augmenting B cell activation and function.

A cascade nanoplatform for intelligent response to tumor microenvironment and collaborative cancer therapy.

Disulfiram (DSF), a new potential anticancer drug, has been shown to exhibit anticancer activity dependent on the formation of CuET, the chelation product of DSF with Cu2+. However, the poor stability of DSF and insufficient physiological concentration of Cu2+ hinder its practical application. To achieve the co-delivery of DSF and Cu2+ while overcoming the inefficiency of single chemotherapy, in this study, a cascade nanoplatform, DSF/Ce6@ZIF-8@CuO2, was constructed by encapsulating DSF and chlorin e6 (Ce6, a photosensitizer) in zeolite imidazole framework-8 (ZIF-8, a nanocarrier) and then loading CuO2, which self-supplied H2O2/O2, onto DSF/Ce6@ZIF-8. By triggering the response of DSF/Ce6@ZIF-8@CuO2 to the acidic tumor microenvironment, encapsulated DSF, Ce6 and CuO2 were released to achieve multimodal synergistic treatment with enhanced DSF chemotherapy and chemodynamic/photodynamic therapy (CDT/PDT). In vitro and animal studies indicated that the designed DSF/Ce6@ZIF-8@CuO2 has strong tumor-inhibitory effects and provides a promising paradigm for designing smart nanoplatforms.

Cumulative Exposure to Oxidized Low-density Lipoprotein is a Potential Predictor for Prognosis in Acute Ischemic Stroke: A Cohort Study.

BACKGROUND: Oxidized Low-Density Lipoprotein (ox-LDL) is crucial in the recrudescence and prognosis of acute ischemic stroke (AIS). We aimed to probe into the influence of cumulative ox-LDL exposure on the 90-day prognosis of AIS. METHODS: Patients with AIS were recruited in this research. AIS severity at admission was estimated with infarct volumes and National Institute of Health Stroke Scale (NIHSS) scores. AIS prognosis was assessed using Modified Rankin Scale (mRS) scores at 90 days and the change in NIHSS scores from admission to discharge. Cumulative ox-LDL exposure was defined as ox-LDL level (pg/mL) multiplied by age(y). Multivariate logistic regression analysis was employed to reveal the correlation between exposure factors and the prognosis of AIS. The prognostic prediction ability of cumulative ox-LDL exposure was compared with cumulative LDL exposure by the receiver operating characteristic curve (ROC). RESULTS: Higher cumulative ox-LDL exposure was related to worse prognosis, including neurological worsening at discharge (NIHSS increasing more than 2 points) (OR = 3.02, 95% CI, 1.30-6.98, P = 0.01) and poor functional prognosis at 90 days (mRS ≥ 3) (OR = 21.21, 95% CI, 4.72-95.36, P < 0.001). As multivariate regression analysis showed, significantly increased cumulative ox-LDL exposure was relevant to poor functional prognosis at 90 days (OR = 9.92, 95% CI, 1.23-79.76, P = 0.031), but not with neurological worsening at discharge (P = 0.414). ROC curve revealed that cumulative ox-LDL exposure had a higher predictive value (AUC = 0.843, P < 0.001) for functional prognosis of AIS than cumulative LDL exposure (AUC = 0.629, P = 0.023). CONCLUSION: Cumulative ox-LDL exposure has a positive correlation with poor prognosis at 90 days of AIS, and has a more accurate predictive ability than cumulative LDL exposure.

Plastic Waste Conversion by Leveraging Renewable Photo/Electro-Catalytic Technologies.

Plastics have revolutionized our lives; however, the exponential growth of their usage has led to a global crisis. More sustainable strategies are needed to address this dilemma and transform the plastics economy from a linearity to a circular model. Herein, we systematically summarize the recent progress in renewable energy-driven plastic conversion strategies, including photocatalysis, electrocatalysis, and their integration. By introducing the significant works, the design principles, mechanisms, and system regulations, we decipher and compare the various aspects of plastic conversion. These approaches show high reactivity and selectivity under environmentally benign conditions and provide alternative reaction pathways for plastic conversion. Plastic upcycling as a chemical feedstock can yield value-added chemicals and fuels, contributing to the establishment of a sustainable and circular economy. Additionally, several innovations in reaction engineering and system designs are presented. Finally, the challenges and perspectives of sustainable energy-driven plastic conversion technologies are comprehensively discussed.

Z-Type Heterojunction MnO2@g-C3N4 Photocatalyst-Activated Peroxymonosulfate for the Removal of Tetracycline Hydrochloride in Water.

A Z-type heterojunction MnO2@g-C3N4 photocatalyst with excellent performance was synthesized by an easy high-temperature thermal polymerization approach and combined with peroxymonosulfate (PMS) oxidation technology for highly efficient degrading of tetracycline hydrochloride (TC). Analysis of the morphological structural and photoelectric properties of the catalysts was achieved through different characterization approaches, showing that the addition of MnO2 heightened visible light absorption by g-C3N4. The Mn1-CN1/PMS system showed the best degradation of TC wastewater, with a TC degradation efficiency of 96.97% following 180 min of treatment. This was an approximate 38.65% increase over the g-C3N4/PMS system. Additionally, the Mn1-CN1 catalyst exhibited excellent stability and reusability. The active species trapping experiment indicated •OH and SO4•- remained the primary active species to degrade TC in the combined system. TC degradation pathways and intermediate products were determined. The Three-Dimensional Excitation-Emission Matrix (3DEEM) was employed for analyzing changes in the molecular structure in TC photocatalytic degradation. The biological toxicity of TC and its degradation intermediates were investigated via the Toxicity Estimation Software Test (T.E.S.T.). The research offers fresh thinking for water environment pollution treatment.

FOXO3a-regulated arginine metabolic plasticity adaptively promotes esophageal cancer proliferation and metastasis.

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor with a poor prognosis due to a lack of early detection. Indeed, the mechanisms underlying ESCC progression remain unclear. Here, we discovered that abnormal arginine metabolism contributes to ESCC progression. Based on transcriptomic and metabolomic analyses, we found that argininosuccinate synthetase 1 (ASS1) and argininosuccinate lyase (ASL) levels were increased in primary tumor tissues but decreased in lymph-metastatic tumor tissues. Intriguingly, FOXO3a was inversely correlated with ASS1 and ASL in primary and metastatic tumor tissues, suggesting that FOXO3a dissimilarly regulates ASS1 and ASL at different stages of ESCC. Silencing ASS1/ASL inhibited primary tumor growth and promoted metastasis. Conversely, overexpression of ASS1/ASL or increased arginine supply promoted tumor proliferation but suppressed metastasis. In addition, FOXO3a activation inhibited primary tumor growth by repressing ASS1 and ASL transcription, whereas inactivation of FOXO3a impeded metastasis by releasing ASS1 and ASL transcription. Together, the finding sheds light on metastatic reprogramming in ESCC.

WOOD: Wasserstein-Based Out-of-Distribution Detection.

The training and testing data for deep-neural-network-based classifiers are usually assumed to be sampled from the same distribution. When part of the testing samples are drawn from a distribution that is sufficiently far away from that of the training samples (a.k.a. out-of-distribution (OOD) samples), the trained neural network has a tendency to make high-confidence predictions for these OOD samples. Detection of the OOD samples is critical when training a neural network used for image classification, object detection, etc. It can enhance the classifier's robustness to irrelevant inputs, and improve the system's resilience and security under different forms of attacks. Detection of OOD samples has three main challenges: (i) the proposed OOD detection method should be compatible with various architectures of classifiers (e.g., DenseNet, ResNet) without significantly increasing the model complexity and requirements on computational resources; (ii) the OOD samples may come from multiple distributions, whose class labels are commonly unavailable; (iii) a score function needs to be defined to effectively separate OOD samples from in-distribution (InD) samples. To overcome these challenges, we propose a Wasserstein-based out-of-distribution detection (WOOD) method. The basic idea is to define a Wasserstein-based score that evaluates the dissimilarity between a test sample and the distribution of InD samples. An optimization problem is then formulated and solved based on the proposed score function. The statistical learning bound of the proposed method is investigated to guarantee that the loss value achieved by the empirical optimizer approximates the global optimum. The comparison study results demonstrate that the proposed WOOD consistently outperforms other existing OOD detection methods.