Caspase activation in response to cytotoxic Rana catesbeiana ribonuclease in MCF-7 cells

AbstractRana catesbeiana ribonuclease (RC-RNase) and onconase were proven to own anti-tumor activity. While molecular determinants of onconase-induced cell death have become more explicit, the RC-RNase-induced death pathway remains presently unknown. Here we demonstrated that RC-RNase-induced molecular cascades in caspase-3-deficient MCF-7 cells did not include activation of initiation caspase-8 and -9. Cleavage timing suggested that procaspase-2 and -6 might be processed by active caspase-7 in MCF-7 cells. Caspase-7 was also responsible for cleavage of the poly(ADP-ribose) polymerase. Furthermore, we reported that overexpression of Bcl-XL could raise the survival rates of MCF-7 cells treated with RC-RNase and onconase

Chaos Synchronization Using Adaptive Dynamic Neural Network Controller with Variable Learning Rates

This paper addresses the synchronization of chaotic gyros with unknown parameters and external disturbance via an adaptive dynamic neural network control (ADNNC) system. The proposed ADNNC system is composed of a neural controller and a smooth compensator. The neural controller uses a dynamic RBF (DRBF) network to online approximate an ideal controller. The DRBF network can create new hidden neurons online if the input data falls outside the hidden layer and prune the insignificant hidden neurons online if the hidden neuron is inappropriate. The smooth compensator is designed to compensate for the approximation error between the neural controller and the ideal controller. Moreover, the variable learning rates of the parameter adaptation laws are derived based on a discrete-type Lyapunov function to speed up the convergence rate of the tracking error. Finally, the simulation results which verified the chaotic behavior of two nonlinear identical chaotic gyros can be synchronized using the proposed ADNNC scheme

CCACK: Efficient Network Coding Based Opportunistic Routing Through Cumulative Coded Acknowledgments

The use of random linear network coding (NC) has significantly simplified the design of opportunistic routing (OR) protocols by removing the need of coordination among forwarding nodes for avoiding duplicate transmissions. However, NC-based OR protocols face a new challenge: How many coded packets should each forwarder transmit? To avoid the overhead of feedback exchange, most practical existing NC-based OR protocols compute offline the expected number of transmissions for each forwarder using heuristics based on periodic measurements of the average link loss rates and the ETX metric. Although attractive due to their minimal coordination overhead, these approaches may suffer significant performance degradation in dynamic wireless environments with continuously changing levels of channel gains, interference, and background traffic. In this paper, we propose CCACK, a new efficient NC-based OR protocol. CCACK exploits a novel Cumulative Coded ACKnowledgment scheme that allows nodes to acknowledge network coded traffic to their upstream nodes in a simple way, oblivious to loss rates, and with practically zero overhead. In addition, the cumulative coded acknowledgment scheme in CCACK enables an efficient credit-based, rate control algorithm. Our experiments on a 22-node 802.11 WMN testbed show that compared to MORE, a state-of-the-art NC based OR protocol, CCACK improves both throughput and fairness, by up to 3.2x and 83%, respectively, with average improvements of 11- 36% and 5.7-8.3%, respectively, for different numbers of concurrent flows. Our extensive simulations show that the gains are actually much higher in large networks, with longer routing paths between sources and destinations

Ring Keratitis Associated With Topical Abuse of a Dilute Anesthetic After Refractive Surgery

Anesthetic toxic keratitis is rare and presents as a ring keratitis, which is often misdiagnosed as Acanthamoeba keratitis. Here, we report an unusual case of toxic keratitis caused by topical abuse of a dilute anesthetic. A 26-year-old woman presented with bilateral corneal edema, ring infiltrates, pigmented keratic precipitate, Descemet's membrane folding, and strong anterior chamber reactions 2 weeks after laser subepithelial keratomileusis surgery. Tracing back her medical history, topical dilute 0.1% proparacaine was prescribed and frequently used for 1 month. Toxic keratitis was suspected. After discontinuation of the topical anesthetic and initiation of treatment with topical 20% autologous serum, complete corneal epithelialization was achieved within 1 week. Corneal infiltrates and anterior chamber reaction gradually subsided. Vision improved from finger counting to 20/20 in the right eye and 20/25 in the left eye, but confocal microscopy showed decreased corneal endothelial cells. Topical abuse of a dilute topical anesthetic can cause severe toxic keratitis and endothelial cell loss. The physician must be aware of the signs of topical anesthetic abuse and should not prescribe even a dilute anesthetic for long-term use. Autologous serum can help in the recovery of toxic keratitis

Innovation Resilience in Cities

Achieving innovation has been a challenging task, as maintaining its momentum is akin to landing on the moon. What are the key ingredients that innovative cities need to possess to sustain their momentum, especially after experiencing economic setbacks?https://dc.suffolk.edu/ciclseries/1001/thumbnail.jp

Prognostic values of a combination of intervals between respiratory illness and onset of neurological symptoms and elevated serum IgM titers in Mycoplasma pneumoniae encephalopathy

Background/PurposeTo retrospectively analyze the clinical manifestations of Mycoplasma pneumoniae (M. pneumoniae)-associated encephalopathy in pediatric patients.MethodsPediatric patients with positive serum anti-M. pneumoniae immunoglobulin M (IgM) were enrolled in this study. Clinical signs and symptoms, laboratory data, neuroimaging findings, and electrophysiological data were reviewed.ResultsOf 1000 patients identified, 11 (1.1%; male:female ratio = 7:4) had encephalopathy and were admitted to the pediatric intensive care unit. Clinical presentation included fever, symptoms of respiratory illness, and gastrointestinal upset. Neurological symptoms included altered consciousness, seizures, coma, focal neurological signs, and personality change. Neuroimaging and electroencephalographic findings were non-specific. Specimens of cerebrospinal fluid (CSF) for M. pneumoniae polymerase chain reaction (PCR) were negative. Higher M. pneumoniae IgM titers and longer intervals between respiratory and CNS manifestations were associated with worse outcomes.ConclusionClinical manifestations of M. pneumoniae-associated encephalopathy were variable. Diagnosis of M. pneumoniae encephalopathy should not rely on CSF detection of M. pneumoniae by PCR. M. pneumoniae IgM titers and intervals between respiratory and CNS manifestations might be possibly related to the prognosis of patients with M. pneumoniae-associated encephalopathy

Effect of hydrogen sulfide on PC12 cell injury induced by high ATP concentration

Purpose: To investigate the potential protective effect of hydrogen sulfide against neural cell damage induced by a high-concentration of adenosine triphosphate (ATP).Methods: PC12 cells were incubated with ATP in order to induce cell damage. The extracellular level of H2S and protein expression of cystathionine-β-synthase (CBS) were determined. The PC12 cells pretreated with NaHS, aminooxyacetic acid (AOAA) and KN-62, prior to further incubation with ATP, and the effect of the treatments on cell viability was investigated.Results: High-concentration ATP induced cell death in PC12 cells, and this was accompanied by markedly increased contents of extracellular H2S and CBS expression (p < 0.05). The ATP-induced cytotoxicity was significantly compromised after pretreatment with H2S. (p < 0.05). The viability of PC12 cells pretreated with NaHS and AOAA was significantly higher than that of PC12 cells treated with ATP alone. In addition, the viability of ATP-treated PC12 cells was further markedly increased after pretreatment with NaHS and KN-62 (p < 0.05).Conclusion: ATP induced a concentration- and time-dependent cytotoxicity in PC12 cells via theendogenous H2S/CBS system. Supplementation with exogenous H2S mitigated the cell damageinduced by high concentration of ATP via a specific mechanism which may be specifically related to P2X7R

Synergism of Rana catesbeiana ribonuclease and IFN-γ triggers distinct death machineries in different human cancer cells

AbstractRana catesbeiana ribonuclease (RC-RNase) possesses tumor-specific cytotoxicity, which can be synergized by IFN-γ. However, it is unclear how RC-RNase and RC-RNase/IFN-γ induce cell death. In this study, we use substrate cleavage assays to systematically investigate RC-RNase- and RC-RNase/IFN-γ-induced caspase activation in HL-60, MCF-7, and SK-Hep-1 cells. We find that RC-RNase and RC-RNase/IFN-γ induce mitochondria-mediated caspase activation in HL-60 and MCF-7 cells but not in SK-Hep-1 cells, although death of SK-Hep-1 cells is closely related to mitochondrial disruptions. Our findings provide evidence that RC-RNase and RC-RNase/IFN-γ can kill different cancer cells by distinct mechanisms. Compared with onconase, RC-RNase seems to harbor a more specific anti-cancer activity

Predicting serum levels of lithium-treated patients: A supervised machine learning approach

Routine monitoring of lithium levels is common clinical practice. This is because the lithium prediction strategies available developed by previous studies are still limited due to insufficient prediction performance. Thus, we used machine learning approaches to predict lithium concentration in a large real-world dataset. Real-world data from multicenter electronic medical records were used in different machine learning algorithms to predict: (1) whether the serum level was 0.6-1.2 mmol/L or 0.0-0.6 mmol/L (binary prediction), and (2) its concentration value (continuous prediction). We developed models from 1505 samples through 5-fold cross-validation and used 204 independent samples to test their performance by evaluating their accuracy. Moreover, we ranked the most important clinical features in different models and reconstructed three reduced models with fewer clinical features. For binary and continuous predictions, the average accuracy of these models was 0.70-0.73 and 0.68-0.75, respectively. Seven features were listed as important features related to serum lithium levels of 0.6-1.2 mmol/L or higher lithium concentration, namely older age, lower systolic blood pressure, higher daily and last doses of lithium prescription, concomitant psychotropic drugs with valproic acid and -pine drugs, and comorbid substance-related disorders. After reducing the features in the three new predictive models, the binary or continuous models still had an average accuracy of 0.67-0.74. Machine learning processes complex clinical data and provides a potential tool for predicting lithium concentration. This may help in clinical decision-making and reduce the frequency of serum level monitoring