EEBR induces Caspase-1-dependent pyroptosis through the NF-κB/NLRP3 signalling cascade in non-small cell lung cancer.

Lung cancer is a leading cause of cancer-related deaths worldwide. Recent studies have identified pyroptosis, a type of programmed cell death, as a critical process in the development and progression of lung cancer. In this study, we investigated the effect of EEBR, a new compound synthesized by our team, on pyroptosis in non-small cell lung cancer cells (NSCLC) and the underlying molecular mechanisms. Our results demonstrated that EEBR significantly reduced the proliferation and metastasis of NSCLC cells in vitro. Moreover, EEBR-induced pyroptosis in NSCLC cells, as evidenced by cell membrane rupture, the release of cytokines such as interleukin-18 and interleukin-1 beta and the promotion of Gasdermin D cleavage in a Caspase-1-dependent manner. Furthermore, EEBR promoted the nuclear translocation of NF-κB and upregulated the protein level of NLRP3. Subsequent studies revealed that EEBR-induced pyroptosis was suppressed by the inhibition of NF-κB. Finally, EEBR effectively suppressed the growth of lung cancer xenograft tumours by promoting NSCLC pyroptosis in animal models. Taken together, our findings suggest that EEBR induces Caspase-1-dependent pyroptosis through the NF-κB/NLRP3 signalling cascade in NSCLC, highlighting its potential as a candidate drug for NSCLC treatment.

Correlation Analysis Between Tumor Deposit and Clinicopathologic Characteristics and Prognosis of Gastric Cancer: A Multicenter Retrospective Study.

BACKGROUND: The mechanism underlying the formation of gastric tumor deposits (TDs) is unclear. We aimed to explore the risk factors for the formation and prognostic value of TDs. METHODS: This retrospective analysis included 781 locally advanced gastric cancer (LAGC) patients from four medical institutions in China, from June 2014 to June 2018. The risk factors for TD formation and prognostic value were determined through univariate and multivariate analyses. RESULTS: Univariate analysis revealed that TD positivity was closely related to tumor diameter, Borrmann classification, differentiation degree, pT stage, pN stage, pTNM stage, and nerve and vascular invasion (p < 0.05). Multivariate logistic regression revealed that tumor diameter ≥ 5 cm (odds ratio [OR] 1.836, 95% confidence interval [CI] 1.165-2.894, p = 0.009) and vascular invasion (OR 2.152, 95% CI 1.349-3.433, p = 0.001) were independent risk factors for TD positivity. Multivariate Cox analysis revealed that TD positivity (OR 1.533, 95% CI 1.101-2.134, p = 0.011), tumor diameter ≥ 5 cm (OR 1.831, 95% CI 1.319-2.541, p < 0.001), pT4a stage (OR 1.652, 95% CI 1.144-2.386, p = 0.007), and vascular invasion (OR 1.458, 95% CI 1.059-2.008, p = 0.021) were independent risk factors for GC prognosis. The 5-year overall and disease-free survival of the TD-positive group showed significant effects among patients in the pT4a and pN3b stages (p < 0.05). CONCLUSIONS: TDs are closely related to tumor diameter and vascular invasion in LAGC patients, and TD positivity is an independent prognostic factor for LAGC patients, especially those at pT4a and pN3b stages.

Fludarabine, cytarabine, and idarubicin with or without venetoclax in patients with relapsed/refractory acute myeloid leukemia.

Treatment options for relapsed and refractory acute myeloid leukemia patients (R/R AML) are limited. This retrospective cohort study compares safety and efficacy of fludarabine, cytarabine, and idarubicin (FLA-IDA) without or with venetoclax (FLAVIDA) in patients with R/R AML. Thirty-seven and 81 patients received one course FLA-IDA with or without a 7-day course of venetoclax, respectively. The overall response rate (ORR) was significantly higher in FLAVIDA compared to FLAIDA- treated patients (78% vs. 47%; P=0.001), while measurable residual disease was negative at a similar proportion in responding patients (50% vs. 57%), respectively. Eighty-one percent and 79% of patients proceeded to allogeneic hematopoietic cell transplantation or donor lymphocyte infusion after FLAVIDA and FLA-IDA, respectively. Event-free and overall survival were similar in FLAVIDA- and FLA-IDA-treated patients. Refractory patients could be salvaged more successfully after FLA-IDA compared to FLAVIDA pretreatment. Neutrophil and platelet recovery times were similar in the venetoclax and the control group. In conclusion, short-term venetoclax in combination with FLA-IDA represents an effective treatment regimen in R/R AML identifying chemosensitive patients rapidly and inducing measurable residual disease-negative remission in a high proportion of R/R AML patients.

The short- and long-term outcomes of laparoscopic D2 lymphadenectomy plus complete mesogastrium excision for lymph node-negative gastric cancer.

BACKGROUND: Patients with T1-3N0M0 gastric cancer (GC) who undergo radical gastrectomy maintain a high recurrence rate. The free cancer cells in the mesogastric adipose connective tissue (Metastasis V) maybe the reason for recurrence in these individuals. We aimed to evaluate whether D2 lymphadenectomy plus complete mesogastrium excision (D2 + CME) was superior to D2 lymphadenectomy with regard to safety and oncological efficacy for T1-3N0M0 GC. METHODS: Patients with T1-3N0M0 GC who underwent radical resection from January 2014 to July 2018 were retrospectively analyzed; there were 323 patients, of whom 185 were in the D2 + CME group and 138 in the D2 group. The primary endpoint was 5-year disease-free survival (DFS). Secondary endpoints include the 5-year overall survival (OS), recurrence pattern, morbidity, mortality, and surgical outcomes. RESULTS: D2 + CME was associated with less intraoperative bleeding loss, a greater number of lymph nodes harvested, and less time to first postoperative flatus, but the postoperative morbidity was similar. The 5-year DFS was 95.6% (95% CI 92.7-98.5%) and 90.4% (95% CI 85.5-95.3%) in the D2 + CME group and the D2 group, respectively, with a hazard ratio (HR) of 0.455 (95% CI 0.188-1.097; p = 0.071). In terms of recurrence patterns, local recurrence was more prone to occur in the D2 group (p = 0.031). Subgroup analysis indicated that for patients with T1b-3N0M0 GC, the 5-year DFS in the D2 + CME group was considerably greater than that in the D2 group (95.3% [95% CI 91.6-99.0%] vs. 87.6% [95% CI 80.7-94.5%], HR 0.369, 95% CI 0.138-0.983; log-rank p = 0.043). CONCLUSION: Laparoscopic D2 + CME for T1-3N0M0 GC is safe and feasible. Furthermore, it not only reduces the local recurrence rate but also improves the 5-year DFS in cases of T1b-3N0M0 GC.

Development and validation of a sensitive liquid chromatography-tandem mass spectrometry method for the assay of 12 substances in rat plasma and its application to rat pharmacokinetics of Epimedium and Psoraleae Fructus herb pair after oral administration.

Epimedium (EM) and Psoraleae Fructus (PF) are a traditional herb combination often used as a fixed form to treat osteoporosis disease in the clinic. However, the intricate interactions of this pair remain unknown. In our study, we undertook a comprehensive examination of their compatibility behaviors. Concurrently, a precise and sensitive quantitation method was successfully developed and validated using liquid chromatography-tandem mass spectrometry for the determination of 12 components. This method was applied in analyzing herbal extracts and biological samples (both in the portal vein and systemic plasma), which was also used to study the pharmacokinetics of the herb pair. The results indicated that the combination of EM and PF enhanced the dissolution of chemical components from PF in extracts, but it had a negligible influence on the contents of the components from EM. On the contrary, the in vivo exposure of the lowly exposed EM flavonoids significantly increased following the combination of EM and PF, whereas the highly exposed psoralen and isopsoralen were greatly reduced. These interactions might be crucial for the synergy and toxicity reduction of the herbal pair in disease treatment, which pave the way for further exploration into the clinical application and pharmacological mechanisms of EM and PF.

Construction of a nomogram based on clinicopathologic features to predict the likelihood of No. 253 lymph node metastasis in rectal cancer patients.

PURPOSE: To explore the high-risk factors for rectal cancer No.253 lymph node metastasis (LNM) and to construct a risk nomogram for the individualized prediction of No.253 LNM. METHODS: This was a retrospective analysis of 425 patients with rectal cancer who underwent laparoscopic-assisted radical surgery. Independent risk factors for rectal cancer No.253 LNM was identified using multivariate logistic regression analysis, and a risk prediction nomogram was constructed based on the independent risk factors. In addition, the performance of the model was evaluated by discrimination, calibration, and clinical benefit. RESULTS: Multivariate logistic regression analysis showed that No.253 lymphadenectasis on CT (OR 10.697, P < 0.001), preoperative T4-stage (OR 4.431, P = 0.001), undifferentiation (OR 3.753, P = 0.004), and preoperative Ca199 level > 27 U/ml (OR 2.628, P = 0.037) were independent risk factors for No.253 LNM. A nomogram was constructed based on the above four factors. The calibration curve of the nomogram was closer to the ideal diagonal, indicating that the nomogram had a better fitting ability. The area under the ROC curve (AUC) was 0.865, which indicated that the nomogram had high discriminative ability. In addition, decision curve analysis (DCA) showed that the model could show better clinical benefit when the threshold probability was between 1% and 50%. CONCLUSION: Preoperative No.253 lymphadenectasis on CT, preoperative T4-stage, undifferentiation, and elevated preoperative Ca199 level were found to be independent risk factors for the No.253 LNM. A predictive model based on these risk factors can help surgeons make rational clinical decisions.

Molecular characterization, spatiotemporal expression, and background adaptation regulation of tyrosinase in loach (Misgurnus anguillicaudatus).

The Poyang Lake region is home to large-blackspot loaches (LBL), small-blackspot loaches (SBL), and non-blackspot loaches (NBL), Misgurnus anguillicaudatus. To investigate the impact of tyrosinase on spot development, the complementary DNAs (cDNA) of tyrosinase in M. anguillicaudatus (designated as Matyr) were cloned using the rapid amplification of cDNA ends (RACE)-PCR method. The full-length cDNA for Matyr was 2020 bp, and the open-reading frame comprised 1617 bp, encoding a predicted protein with 538 amino acids. Phylogenetic studies revealed that MaTyr was first grouped with Tyr of Triplophysa tibetana and Leptobotia taeniops, and then Tyr of other cyprinid fish. The quantitative reverse-transcription-PCR results show that Matyr was highly expressed in the muscle, caudal fin, and dorsal skin. The Matyr gene's messenger RNA expression pattern steadily increased from the fertilized ovum period to the somitogenesis period, and from the muscle effect stage to 6 days after fertilization, it considerably increased (p < 0.01). The Matyr hybridization signals with similar location could be found in all developmental stages of three kinds of loaches using whole-mount in situ hybridization (WISH) technology and were the strongest during the organ development period and melanin formation period. Dot hybridization signals in LBLs rapidly spread to the back of the body beginning at the period when the eyes first formed melanin, and their dimensions were larger than those of NBLs during the same time period. The body color of loaches could change reversibly with black/white background adaptation. The α-msh, mitfa, and tyr are mainly expressed in loaches adapted with a black background. Tyr gene could be involved in the development of blackspots and body color polymorphism, and contribute to organ development in the loach.

Native Mass Spectrometry Quantitation of α2-3-Linked N-Acetylneuraminic Acid Content of Prostate-Specific Antigen: An Accurate Liquid Biopsy for Clinically Significant Prostate Cancer.

Application of the prostate-specific antigen (PSA) test, which measures PSA levels in blood, is standard in prostate cancer (PCa) screening. However, because PSA levels may be elevated for reasons other than PCa, it leads to high rates of misdiagnosis and overtreatment. Recently, alteration in the N-glycan sialylation of PSA, specifically increased levels of α2-3-linked N-acetylneuraminic acid (α2-3-Neu5Ac or α2-3-sialic acid), was identified as a potential biomarker for clinically significant PCa. Here, we introduce a robust top-down native mass spectrometry (MS) approach, performed using a combination of α2-3-Neu5Ac-specific and nonspecific neuraminidases and employing center-of-mass monitoring (CoMMon), for quantifying the levels of α2-3-Neu5Ac as a fraction of total N-linked Neu5Ac present on PSA extracted from blood serum. To illustrate the potential of the assay for clinical diagnosis and disease staging of PCa, the percentages of α2-3-Neu5Ac on PSA (%α23PSA) in the serum of low-grade (International Society of Urological Pathology Grade Group/GG1), intermediate-grade (GG2), and high-grade (GG3,4,5) PCa individuals were measured. We observed a high sensitivity (85.5%) and specificity (84.6%) for discrimination of GG1 from clinically significant GG2-5 patients when using a %α23PSA test cut-off of 28.0%. Our results establish that the %α23PSA in blood serum PSA, which can be precisely measured in a non-invasive manner with our dual neuraminidase native MS/CoMMon assay, can discriminate between clinically significant PCa (GG2-5) and low-grade PCa (GG1). Such discrimination has not been previously achieved and represents an important clinical need. This assay could greatly improve the standard PSA test and serve as a valuable PCa diagnostic tool.

Nomogram to Predict Recurrence and Guide a Pragmatic Surveillance Strategy After Resection of Hepatoid Adenocarcinoma of the Stomach: A Retrospective Multicenter Study.

BACKGROUND: An accurate recurrence risk assessment system and surveillance strategy for hepatoid adenocarcinoma of the stomach (HAS) remain poorly defined. This study aimed to develop a nomogram to predict postoperative recurrence of HAS and guide individually tailored surveillance strategies. METHODS: The study enrolled all patients with primary HAS who had undergone curative-intent resection at 14 institutions from 2004 to 2019. Clinicopathologic variables with statistical significance in the multivariate Cox regression were incorporated into a nomogram to build a recurrence predictive model. RESULTS: The nomogram of recurrence-free survival (RFS) based on independent prognostic factors, including age, preoperative carcinoembryonic antigen, number of examined lymph nodes, perineural invasion, and lymph node ratio, achieved a C-index of 0.723 (95% confidence interval [CI], 0.674-0.772) in the whole cohort, which was significantly higher than those of the eighth American Joint Committed on Cancer (AJCC) staging system (C-index, 0.629; 95% CI, 0.573-0.685; P < 0.001). The nomogram accurately stratified patients into low-, middle-, and high-risk groups of postoperative recurrence. The postoperative recurrence risk rates for patients in the middle- and high-risk groups were respectively 3 and 10 times higher than for the low-risk group. The patients in the middle- and high-risk groups showed more recurrence and metastasis, particularly multiple site metastasis, within 36 months after the operation than those in the low-risk group (low, 2.2%; middle, 8.6%; high, 24.0%; P = 0.003). CONCLUSIONS: The nomogram achieved good prediction of postoperative recurrence for the patients with HAS after radical resection. For the middle- and high-risk patients, more active surveillance and targeted examination methods should be adopted within 36 months after the operation, particularly for liver and multiple metastases.

The short- and long-term effect of laparoscopic total gastrectomy in D2 radical treatment combined with spleno-pancreatectomy under membrane anatomy.

OBJECTIVE: To explore the short- and long-term effect of laparoscopic total gastrectomy in D2 radical treatment combined with spleno-pancreatectomy under membrane anatomy. METHODS: From June 2013 to June 2018, 70 patients with gastric cancer underwent total gastrectomy combined with spleno-pancreatectomy involving 37 cases in laparoscopy group and 33 cases in laparotomy group. The intraoperative and postoperative conditions of patients in the two groups were compared and analyzed. RESULTS: In the laparoscopy group, the operation time and the number of positive lymph node dissection was similar to the laparotomy group. Statistical difference was found in intraoperative bleeding [(79.19 ± 39.63)ml vs (214.39 ± 152.47)m1], the number of lymph node dissection [(47.27 ± 13.94) vs (35.45 ± 9.81)], the first time of aerofluxus [(2.92 ± 0.76)d vs (3.76 ± 1.09)d], the first fluid intake time [(7.49 ± 0.96)d vs (8.27 ± 1.91)d] and the postoperative hospital stay [(11.95 ± 1.90)d vs (15.39 ± 4.07)d] (P < 0.05), So the laparoscopy group was significantly superior to the laparotomy group. The incidences of postoperative complications in laparoscopy group and the laparotomy group were 35.13% and 27.27%, and the difference was not statistically significant. (P > 0.05). No stark difference in postoperative complications of Clavien-Dindo Classification (P > 0.05). The K-M survival curve showed no significant difference in 3-year overall survival (OS) and 3-year disease-free survival (DFS) between the two groups (P > 0.05). CONCLUSION: The laparoscopic total gastrectomy in D2 radical treatment combined with spleno-pancreatectomy under membrane anatomy is feasible and safe, which can remove more perigastric lymph nodes. With advantages of less intraoperative blood loss and fast postoperative recovery, it cannot increase postoperative complications and long-term survival are comparable to open surgery.

The short- and long-term effect of membrane anatomy-guided laparoscopic D2 lymphadenectomy plus regional complete mesogastrium excision for locally advanced gastric cancer.

OBJECTIVE: Retrospectively analyzed the short- and long-term efficacy between laparoscopic D2 lymphadenectomy plus regional complete mesogastrium excision (D2 + rCME) and traditional laparoscopic D2 in the treatment of patients with locally advanced gastric cancer (LAGC), in order to obtain more evidence for D2 + rCME gastrectomy. METHODS: A total of 599 LAGC patients who underwent laparoscopy-assisted radical gastrectomy from January 2014 to December 2019, including 367 cases in the D2 + rCME group and 232 cases in the D2 group. Intraoperative and postoperative clinicopathological parameters, postoperative complications and long-term survival in the two groups were statistically analyzed. RESULTS: No significant differences in the positive rate of mesogastric tumor deposits, the number of positive lymph nodes and postoperative length of stay were found between the two groups (P > 0.05). In the D2 + rCME group, intraoperative blood loss was significantly reduced (84.20 ± 57.64 ml vs. 148.47 ± 76.97 ml, P < 0.001), the time to first postoperative flatus and first liquid diet intake were significantly shortened (3[2-3] days vs. 3[3-3] days, P < 0.001; 7[7-8] days vs. 8[7-8] days, P < 0.001), and the number of lymph nodes dissected was greater (43.57 ± 16.52 pieces vs. 36.72 ± 13.83 pieces, P < 0.001). The incidence of complications did not significantly differ between the D2 + rCME group (20.7%) and D2 group (19.4%) (P > 0.05). Although there was no statistically difference in 3-year OS and DFS between the two groups. However, the trend was better in D2 + rCME group. In subgroup analysis, patients with positive tumor deposits (TDs) in the D2 + rCME group had significantly better 3-year DFS compared With D2 group (P < 0.05). CONCLUSION: Laparoscopic D2 + rCME is safe and feasible for the treatment of LAGC and is characterized by less bleeding, greater lymph node dissection and rapid recovery, without increasing postoperative complications. D2 + rCME group showed a better trend of long-term efficacy, especially significant beneficial for LAGC patients who with positive TDs.

A prediction nomogram for postoperative gastroparesis syndrome in right colon cancer: a retrospective study.

PURPOSE: To investigate the high-risk factors for postoperative gastroparesis syndrome (PGS) in right colon cancer and to build a prediction nomogram for personalized prediction of PGS. METHODS: Our study retrospectively analyzed 361 patients with right colon cancer who underwent right hemicolectomy at The First Hospital of Putian City in Fujian Province, China and who were hospitalized between January 2012 and July 2022. Multivariate logistic regression was used to determine the independent risk factors for PGS and to establish a nomogram model. Furthermore, discrimination, calibration, and clinical benefits were used to evaluate the model. RESULTS: The multivariate logistic regression revealed that dissection of the subpyloric lymph nodes (No. 206 lymph node) (OR 5.242, P = 0.005), preoperative fasting blood glucose level (OR 3.708, P = 0.024), preoperative albumin level (OR 3.503, P = 0.020), and total operative time (OR 4.648, P = 0.014) were independent risk factors for PGS. Based on the above four factors, the area under the ROC curve (AUC) and C-index of the nomogram were 0.831. The prediction nomogram's calibration curve was closer to the ideal diagonal, and the Hosmer‒Lemeshow test indicated that the nomogram fit well (P = 0.399). Moreover, the decision curve analysis revealed that the model can present better clinical benefits when the threshold probability was between 1 and 28%, and the internal validation verified the dependability of the model (C-index = 0.948). CONCLUSIONS: A risk prediction nomogram based on perioperative factors provided the physician with a simple, visual, and efficient tool for the prediction and management of PGS in right colon cancer.

Comparative study on the gene expression of corticosterone metabolic enzymes in embryonic tissues between Tibetan and broiler chickens.

Glucocorticoids (GCs) are an essential mediator hormone that can regulate animal growth, behavior, the phenotype of offspring, and so on, while GCs in poultry are predominantly corticosterones. The biological activity of GCs is mainly regulated by the intracellular metabolic enzymes, including 11ß-hydroxysteroid dehydrogenases 1 (11ß-HSD1), 11ß-hydroxysteroid dehydrogenases 2 (11ß-HSD2), and 20-hydroxysteroid dehydrogenase (20-HSD). To investigate the embryonic mechanisms of phenotypic differences between breeds, we compared the expression of corticosterone metabolic enzyme genes in the yolk-sac membrane and chorioallantoic membrane (CAM). We described the tissue distribution and ontogenic patterns of corticosterone metabolic enzymes during embryonic incubation between Tibetan and broiler chickens. Forty fertilized eggs from Tibetan and broiler chickens were incubated under hypoxic and normoxic conditions, respectively. Real-time fluorescence quantitative PCR was used to examine the expression of 11ß-HSD1/2, and 20-HSD mRNA in embryonic tissues. The results showed that the expression levels of yolk-sac membrane mRNA of 11ß-HSD2 and 20-HSD in Tibetan chickens on E14 (embryonic day of 14) were significantly lower than those of broiler chickens (P < 0.05), and these genes expression of CAM in Tibetan chickens were higher than those of broiler chickens (P < 0.05). In addition, the three genes in the yolk-sac membrane and CAM were followed by a down-regulation on E18 (embryonic day of 18). The 11ß-HSD1 and 11ß-HSD2 genes followed a similar tissue-specific pattern: the expression level was more abundantly in the liver, kidney, and intestine, with relatively lower abundance in the hypothalamus and muscle, and the expression level of 20-HSD genes in all tissues tested was higher. In the liver, 20-HSD of both Tibetan and broiler chickens showed different ontogeny development patterns, and hepatic mRNA expression of 20-HSD in broiler chickens was significantly higher than that of Tibetan chickens of the same age from E14 to E18 (P < 0.05). This study preliminarily revealed the expression levels of cortisol metabolic genes in different tissues during the development process of Tibetan and broiler chicken embryos. It provided essential information for in-depth research of the internal mechanism of maternal GCs programming on offspring.

FGF1 promotes the differentiation of goat intramuscular and subcutaneous preadipocytes.

Fibroblast growth factor 1(FGF1) has been proved to bind to specific signal molecules and activate intracellular signal transduction, leading to proliferation or differentiation of cells. However, the role of FGF1 in goat adipocytes is still unclear. Here, we investigated its role in lipogenesis of goats, which depends on the activation of FGFRs. In goat intramuscular and subcutaneous adipocytes, we observed that adipocytes accumulation was inhibited by interfering of FGF1, the expression of C/EBPα, C/EBPß, LPL, Pref-1, PPARγ, AP2, KLF4, KLF6, KLF10 and KLF17 were significantly down-regulated (p < 0.05). When the FGF1 was up-regulated, the opposite result was found, while the expression of C/EBPß, LPL, PPARγ, SREBP1, AP2, KLF4, KLF7, KLF15, KLF16 and KLF17 were increased significantly (p < 0.05) in goat intramuscular and subcutaneous adipocytes. The expression level of FGFR1 was significantly and decreased with the interference of FGF1, and increased with the overexpression of FGF1. But in goat subcutaneous adipocytes, only the expression of FGFR2 was consistent with the expression of FGF1. Interference methods confirmed that FGFR1 or FGFR2 and FGF1 have the similarly promoting function in adipocytes differentiation. With the co-transfection technology, we confirmed that FGF1 promoted the differentiation of intramuscular and subcutaneous adipocytes might via FGFR1 or FGFR2, respectively.

Mass Spectrometry-Based Shotgun Glycomics Using Labeled Glycan Libraries.

Mass spectrometry-based shotgun glycomics (MS-SG) is a rapid, sensitive, label-, and immobilization-free approach for the discovery of natural ligands of glycan-binding proteins (GBPs). To perform MS-SG, natural libraries of glycans derived from glycoconjugates in cells or tissues are screened against a target GBP using catch-and-release electrospray ionization mass spectrometry (CaR-ESI-MS). Because glycan concentrations are challenging to determine, ligand affinities cannot be directly measured. In principle, relative affinities can be ranked by combining CaR-ESI-MS data with relative concentrations established by hydrophilic interaction liquid chromatography (HILIC) performed on the fluorophore-labeled glycan library. To validate this approach, as well as the feasibility of performing CaR-ESI-MS directly on labeled glycans, libraries of labeled N-glycans extracted from the human monocytic U937 cells or intestinal tissues were labeled with 2-aminobenzamide (2-AB), 2-aminobenzoic acid (2-AA), or procainamide (proA). The libraries were screened against plant and human GBPs with known specificities for α2-3- and α2-6-linked sialosides and quantified by HILIC. Dramatic differences, in some cases, were found for affinity rankings obtained with libraries labeled with different fluorophores, as well as those produced using the combined unlabeled/labeled library approach. The origin of these differences could be explained by differential glycan labeling efficiencies, the impact of specific labels on glycan affinities for the GBPs, and the relative efficiency of release of ligands from GBPs in CaR-ESI-MS. Overall, the results of this study suggest that the 2-AB(CaR-ESI-MS)/2-AB(HILIC) combination provides the most reliable description of the binding specificities of GBPs for N-glycans and is recommended for MS-SG applications.

Deep-Neural-Network-Based Modelling of Longitudinal-Lateral Dynamics to Predict the Vehicle States for Autonomous Driving.

Multibody models built in commercial software packages, e.g., ADAMS, can be used for accurate vehicle dynamics, but computational efficiency and numerical stability are very challenging in complex driving environments. These issues can be addressed by using data-driven models, owing to their robust generalization and computational speed. In this study, we develop a deep neural network (DNN) based model to predict longitudinal-lateral dynamics of an autonomous vehicle. Dynamic simulations of the autonomous vehicle are performed based on a semirecursive multibody method for data acquisition. The data are used to train and test the DNN model. The DNN inputs include the torque applied on wheels and the vehicle's initial speed that imitates a double lane change maneuver. The DNN outputs include the longitudinal driving distance, the lateral driving distance, the final longitudinal velocities, the final lateral velocities, and the yaw angle. The predicted vehicle states based on the DNN model are compared with the multibody model results. The accuracy of the DNN model is investigated in detail in terms of error functions. The DNN model is verified within the framework of a commercial software package CarSim. The results demonstrate that the DNN model predicts accurate vehicle states in real time. It can be used for real-time simulation and preview control in autonomous vehicles for enhanced transportation safety.

Evaluation of Different Bearing Fault Classifiers in Utilizing CNN Feature Extraction Ability.

In aerospace, marine, and other heavy industries, bearing fault diagnosis has been an essential part of improving machine life, reducing economic losses, and avoiding safety problems caused by machine bearing failures. Most existing bearing fault diagnosis methods face challenges in extracting the fault features from raw bearing fault data. Compared with traditional methods for bearing fault characteristics extraction, deep neural networks can automatically extract intrinsic features without expert knowledge. The convolutional neural network (CNN) was utilized most widely in extracting representative features of bearing faults. Fundamental to this, the hybrid models based on the CNN and individual classifiers were proposed to diagnose bearing faults. However, CNN may not be suitable for all bearing fault classifiers. It is crucial to identify the classifiers which can maximize the CNN feature extraction ability. In this paper, four hybrid models based on CNN were built, and their fault detection accuracy and efficiency were compared. The comparative analysis showed that the random forest (RF) and support vector machine (SVM) could make full use of the CNN feature extraction ability.

An Improved Deep Neural Network Model of Intelligent Vehicle Dynamics via Linear Decreasing Weight Particle Swarm and Invasive Weed Optimization Algorithms.

We propose an improved DNN modeling method based on two optimization algorithms, namely the linear decreasing weight particle swarm optimization (LDWPSO) algorithm and invasive weed optimization (IWO) algorithm, for predicting vehicle's longitudinal-lateral responses. The proposed improved method can restrain the solutions of weight matrices and bias matrices from falling into a local optimum while training the DNN model. First, dynamic simulations for a vehicle are performed based on an efficient semirecursive multibody model for real-time data acquisition. Next, the vehicle data are processed and used to train and test the improved DNN model. The vehicle responses, which are obtained from the LDWPSO-DNN and IWO-DNN models, are compared with the DNN and multibody results. The comparative results show that the LDWPSO-DNN and IWO-DNN models predict accurate longitudinal-lateral responses in real-time without falling into a local optimum. The improved DNN model based on optimization algorithms can be employed for real-time simulation and preview control in intelligent vehicles.

Adaptive Contrastive Learning with Label Consistency for Source Data Free Unsupervised Domain Adaptation.

Unsupervised domain adaptation, which aims to alleviate the domain shift between source domain and target domain, has attracted extensive research interest; however, this is unlikely in practical application scenarios, which may be due to privacy issues and intellectual rights. In this paper, we discuss a more challenging and practical source-free unsupervised domain adaptation, which needs to adapt the source domain model to the target domain without the aid of source domain data. We propose label consistent contrastive learning (LCCL), an adaptive contrastive learning framework for source-free unsupervised domain adaptation, which encourages target domain samples to learn class-level discriminative features. Considering that the data in the source domain are unavailable, we introduce the memory bank to store the samples with the same pseudo label output and the samples obtained by clustering, and the trusted historical samples are involved in contrastive learning. In addition, we demonstrate that LCCL is a general framework that can be applied to unsupervised domain adaptation. Extensive experiments on digit recognition and image classification benchmark datasets demonstrate the effectiveness of the proposed method.

A New Deep Model for Detecting Multiple Moving Targets in Real Traffic Scenarios: Machine Vision-Based Vehicles.

When performing multiple target detection, it is difficult to detect small and occluded targets in complex traffic scenes. To this end, an improved YOLOv4 detection method is proposed in this work. Firstly, the network structure of the original YOLOv4 is adjusted, and the 4× down-sampling feature map of the backbone network is introduced into the neck network of the YOLOv4 model to splice the feature map with 8× down-sampling to form a four-scale detection structure, which enhances the fusion of deep and shallow semantics information of the feature map to improve the detection accuracy of small targets. Then, the convolutional block attention module (CBAM) is added to the model neck network to enhance the learning ability for features in space and on channels. Lastly, the detection rate of the occluded target is improved by using the soft non-maximum suppression (Soft-NMS) algorithm based on the distance intersection over union (DIoU) to avoid deleting the bounding boxes. On the KITTI dataset, experimental evaluation is performed and the analysis results demonstrate that the proposed detection model can effectively improve the multiple target detection accuracy, and the mean average accuracy (mAP) of the improved YOLOv4 model reaches 81.23%, which is 3.18% higher than the original YOLOv4; and the computation speed of the proposed model reaches 47.32 FPS. Compared with existing popular detection models, the proposed model produces higher detection accuracy and computation speed.