4-Coumarate-CoA ligase (4-CL) enhances flavonoid accumulation, lignin synthesis, and fruiting body formation in Ganoderma lucidum.

It is now understood that 4-Coumarate-CoA ligases (4-CL) are pivotal in bridging the phenylpropanoid metabolic pathway and the lignin biosynthesis pathway in plants. However, limited information on 4-CL genes and their functions in fungi is available. In this study, we cloned the 4-CL gene (Gl21040) from Ganoderma lucidum, which spans 2178 bp and consists of 10 exons and 9 introns. We also developed RNA interference and overexpression vectors for Gl21040 to investigate its roles in G. lucidum. Our findings indicated that in the Gl21040 interference transformants, 4-CL enzyme activities decreased by 31 %-57 %, flavonoids contents decreased by 10 %-22 %, lignin contents decreased by 20 %-36 % compared to the wild-type (WT) strain. Conversely, in the Gl21040 overexpression transformants, 4-CL enzyme activity increased by 108 %-143 %, flavonoids contents increased by 8 %-37 %, lignin contents improved by 15 %-17 % compared to the WT strain. Furthermore, primordia formation was delayed by approximately 10 days in the Gl21040-interferenced transformants but occurred 3 days earlier in the Gl21040-overexpressed transformants compared to the WT strain. These results underscored the involvement of the Gl21040 gene in flavonoid synthesis, lignin synthesis, and fruiting body formation in G. lucidum.

Proportional-Integral Observer-Based State Estimation for Singularly Perturbed Complex Networks With Cyberattacks.

This article investigates the asynchronous proportional-integral observer (PIO) design issue for singularly perturbed complex networks (SPCNs) subject to cyberattacks. The switching topology of SPCNs is regulated by a nonhomogeneous Markov switching process, whose time-varying transition probabilities are polytope structured. Besides, the multiple scalar Winner processes are applied to character the stochastic disturbances of the inner linking strengths. Two mutually independent Bernoulli stochastic variables are exploited to characterize the random occurrences of cyberattacks. In a practical viewpoint, by resorting to the hidden nonhomogeneous Markov model, an asynchronous PIO is formulated. Under such a framework, by applying the Lyapunov theory, sufficient conditions are established such that the augmented dynamic is mean-square exponentially ultimately bounded. Finally, the effectiveness of the theoretical results is verified by two numerical simulations.

Outlier-Resistant State Estimation for Singularly Perturbed Complex Networks With Nonhomogeneous Sojourn Probabilities.

This study investigates an outlier-resistant state estimation problem for singularly perturbed complex networks (SPCNs) with sojourn probabilities and randomly occurring coupling strengths. Aiming at better describing the dynamic behavior of the network topology for SPCNs, a novel switching law associated with the time-varying sojourn probabilities is developed, and the variation of sojourn probabilities is arranged by a high-level deterministic switching signal. Meanwhile, a sequence of mode-dependent variables is employed to describe the randomly occurring coupling strength. Subsequently, to alleviate the side effects from possible measurement outliers, a dynamic saturation function-based state estimator is designed, whose saturation level is adaptively varying based on previous estimation errors. In virtue of Lyapunov theory and mode-dependent average dwell-time strategy, it can be verified that the resulting dynamics is stochastic H∞ finite-time bounded. To this end, a simulation example is presented to show the validity of the proposed estimator design method.

Modeling Not-Reached Items in Cognitive Diagnostic Assessments.

In cognitive diagnostic assessments with time limits, not-reached items (i.e., continuous nonresponses at the end of tests) frequently occur because examinees drop out of the test due to insufficient time. Oftentimes, the not-reached items are related to examinees' specific cognitive attributes or knowledge structures. Thus, the underlying missing data mechanism of not-reached items is non-ignorable. In this study, a missing data model for not-reached items in cognitive diagnosis assessments was proposed. A sequential model with linear restrictions on item parameters for missing indicators was adopted; meanwhile, the deterministic inputs, noisy "and" gate model was used to model the responses. The higher-order structure was used to capture the correlation between higher-order ability parameters and dropping-out propensity parameters. A Bayesian Markov chain Monte Carlo method was used to estimate the model parameters. The simulation results showed that the proposed model improved diagnostic feedback results and produced accurate item parameters when the missing data mechanism was non-ignorable. The applicability of our model was demonstrated using a dataset from the Program for International Student Assessment 2018 computer-based mathematics cognitive test.

Proportional-Integral Observer-Based State Estimation for Markov Memristive Neural Networks With Sensor Saturations.

This article investigates the resilient proportional-integral observer (PIO) problem for Markov switching memristive neural networks (MSMNNs) with randomly occurring sensor saturation within a finite-time interval. The Markov switching of memristive neural networks is regulated by a higher level deterministic switching signal, whose transition probabilities are piecewise time-varying and can be depicted by the average dwell-time strategy. Meanwhile, a Bernoulli stochastic process associated with an uncertain packet arriving rate is adopted to describe the randomly occurring sensor saturation. The aim is to design a resilient PIO such that the augmented dynamic has the property of stochastic finite-time boundedness while meeting the desired performance index. By applying the Lyapunov method and the average dwell-time scheme, sufficient criteria are established for MSMNNs, and a unified design method is presented for the existence of the PIO. Lastly, the attained theoretical results are validated via a numerical simulation.

Early aEEG can predict neurodevelopmental outcomes at 12 to 18 month of age in VLBWI with necrotizing enterocolitis: a cohort study.

BACKGROUND: Studies have shown that neurological damage is common in necrotizing enterocolitis (NEC) survivors. The purpose of the study was to investigate the predictive value of amplitude-integrated electroencephalogram (aEEG) for neurodevelopmental outcomes in preterm infants with NEC. METHODS: Infants with NEC were selected, and the control group was selected based on 1:1-2 pairing by gestational age. We performed single-channel (P3-P4) aEEG in the two groups. The Burdjalov scores were compared between the two groups. Cranial magnetic resonance imaging (MRI) was performed several months after birth. The neurological outcomes at 12 to 18 months of age were compared with the Gesell Developmental Schedules (GDS). The predictive value of aEEG scores for neurodevelopmental delay was calculated. RESULTS: There was good consistency between the two groups regarding general conditions. In the 1st aEEG examination, the patients in NEC group had lower Co (1.0 (0.0, 2.0) vs. 2.0 (2.0, 2.0), P = 0.001), Cy (1.0 (0.0, 2.0) vs. 3.0 (3.0, 4.0), P < 0.001), LB (1.0 (0.0, 2.0) vs. 2.0 (2.0, 2.0), P < 0.001), B (1.0 (1.0, 2.0) vs. 3.0 (3.0, 3.5), P < 0.001) and T (3.0 (2.0, 8.0) vs. 10.0 (10.0, 11.5), P < 0.001), than the control group. Cranial MRI in NEC group revealed a widened interparenchymal space with decreased myelination. The abnormality rate of cranial MRI in the NEC group was higher than that in the control group (P = 0.001). The GDS assessment indicated that NEC children had inferior performance and lower mean scores than the control group in the subdomains of gross motor (71 (SD = 6.41) vs. 92 (SD = 11.37), P < 0.001), fine motor (67 (SD = 9.34) vs. 96 (SD = 13.69), adaptive behavior (76 (SD = 9.85) vs. 95 (SD = 14.38), P = 0.001), language (68 (SD = 12.65) vs. 95 (SD = 11.41), P < 0.001), personal-social responses (80 (SD = 15.15) vs. 93(SD = 14.75), P = 0.037) and in overall DQ (72 (SD = 8.66) vs. 95 (SD = 11.07), P < 0.001). The logistic binary regression analysis revealed that the NEC patients had a significantly greater risk of neurodevelopmental delay than the control group (aOR = 27.00, 95% CI = 2.561-284.696, P = 0.006). Confirmed by Spearman's rank correlation analysis, neurodevelopmental outcomes were significantly predicted by the 1st aEEG Burdjalov score (r = 0.603, P = 0.001). An abnormal 1st Burdjalov score has predictive value for neurodevelopmental delay with high specificity (84.62%) and positive predictive value (80.00%). CONCLUSIONS: Children with NEC are more likely to develop neurodevelopmental delay. There is high specificity and PPV of early aEEG in predicting neurodevelopmental delay.

Analysis of the clinical manifestations and 18F-FDG PET-CT findings in 40 patients with histiocytic necrotizing lymphadenitis.

ABSTRACT: Histiocytic necrotizing lymphadenitis (HNL) is a rare, benign, and self-limiting inflammatory disease that mainly involves the lymph nodes. There is a lack of large sample studies concerning the clinical manifestations and imaging features of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) of HNL.The clinical symptoms, laboratory examination results, 18F-FDG PET/CT imaging features, and treatment outcome were investigated in this retrospective study.A total of 40 HNL patients were recruited. The onset age was between 14 and 65 years, with a median of 25 years. The white blood cell count was 3.9 (2.9, 7.1) × 109/L, C-reactive protein level was 20.2 (6.6, 63.8) mg/L, erythrocyte sedimentation rate was 29.0 (18.0,45.0) mm/h, and ferritin was 616.5 (205.6, 2118.1) ng/mL. An abnormal liver function was observed in 23 patients. 18F-FDG PET-CT showed that an abnormal lymph node metabolism was observed in 38 patients, among which the highest 18F-FDG maximal standard uptake value (SUVmax) of the lymph nodes ranged between 3.4 and 41.9; the nodes were mainly distributed in the neck and axilla regions. Meanwhile, a total of 2502 lymph nodes (721 lymph nodes with a short axis greater than 10 mm) were found in the 38 patients, including 1837 lymph nodes with an 18F-FDG SUVmax ≥ 2.5. The 18F-FDG SUVmax of the spleen ranged from 2.5 to 9.2 in 20 patients, while that of central and peripheral bone marrow ranged from 2.7 to 36.0 in 30 patients. After follow-up for an average period of 1 month, the symptoms improved after prednisone treatment.HNL often occurs in adolescents. Scanning with 18F-FDG PET/CT showed that most patients had multiple involved lymph nodes that were hypermetabolic, and only few lymph nodes are enlarged. Besides, the spleen or central and peripheral bone marrow could sometimes be hypermetabolic. Glucocorticoid treatment for the HNL patients is effective.

Upregulation of microRNA­337 promotes the proliferation of endometrial carcinoma cells via targeting PTEN.

Endometrial carcinoma (EC) is a common malignancy in females. MicroRNAs (miRs) are a class of non­coding RNA that regulate a wide variety of cellular processes, and are important in the development of multiple types of malignancy. In the present study, cancerous and adjacent non­cancerous normal tissue samples were collected from 24 patients diagnosed with EC. Reverse transcription quantitative polymerase chain reaction was performed on the tissue samples to determine the expression levels of six candidate miRs. These miRs have been previously reported to be differentially expressed in EC; however, the present study observed that only miR­337 was differentially expressed. In addition, the current study identified phosphatase and tensin homolog (PTEN) as a target of miR­337 using computational analysis and a luciferase assay. EC cells transfected with miR­337 mimics and anti­PTEN small interfering RNA demonstrated significantly decreased expression of PTEN, markedly increased proliferation and inhibition of cell apoptosis. The results indicate that miR­337 is oncogenic in EC cells, as it suppresses PTEN expression. This may facilitate the development of miR­based prevention or treatment strategies for EC.

Ginsenoside­Rg5 induces apoptosis and DNA damage in human cervical cancer cells.

Panax ginseng is traditionally used as a remedy for cancer, inflammation, stress and aging, and ginsenoside­Rg5 is a major bioactive constituent of steamed ginseng. The present study aimed to evaluate whether ginsenoside­Rg5 had any marked cytotoxic, apoptotic or DNA­damaging effects in human cervical cancer cells. Five human cervical cancer cell lines (HeLa, MS751, C33A, Me180 and HT­3) were used to investigate the cytotoxicity of ginsenoside­Rg5 using a 3­(4,5­dimethylthiazol­2­yl)­2,5­diphenyltetrazolium bromide assay. Additionally, the effects of ginsenoside­Rg5 on the apoptosis of HeLa and MS751 cells were detected using DNA ladder assays and flow cytometry. DNA damage was assessed in the HeLa and MS751 cells using alkaline comet assays and by detection of γH2AX focus formation. The HeLa and MS751 cells were significantly more sensitive to ginsenoside­Rg5 treatment compared with the C­33A, HT­3 and Me180 cells. As expected, ginsenoside­Rg5 induced significant concentration­ and time­dependent increases in apoptosis. In addition, ginsenoside­Rg5 induced significant concentration­dependent increases in the level of DNA damage compared with the negative control. Consistent with the comet assay data, the percentage of γH2AX­positive HeLa and MS751 cells also revealed that ginsenoside­Rg5 caused DNA double­strands to break in a concentration­dependent manner. In conclusion, ginsenoside­Rg5 had marked genotoxic effects in the HeLa and MS751 cells and, thus, demonstrates potential as a genotoxic or cytotoxic drug for the treatment of cervical cancer.