Inhibitory effect of d-Tryptophan on the spoilage potential of Shewanella baltica and Pseudomonas fluorescens and its potential application in salmon fillet preservation.

In this study, we found the inhibitory effect of d-Tryptophan (d-Trp) on the bacterial growth and spoilage potential of P. fluorescens and S. baltica. The effectiveness of d-Trp in bacterial growth inhibition was highly dependent on environmental NaCl concentrations. The growth/no growth models were developed to clarify the relationship between salt and d-Trp concentrations for optimal growth-inhibitory effect. It showed that higher levels of NaCl (>3.5%) with d-Trp (>15 mM) are required for growth inhibition. The d-Trp treatment combined with NaCl also retarded the psychrotrophic growth and reduced the respiratory active bacteria at low temperature, indicating that the inhibitory effect of d-Trp might be associated with the tolerance to osmotic and cold stress. Furthermore, the treatment d-Trp combined NaCl (artificial seawater) on salmon fillets was investigated. During refrigerated storage, the d-Trp treated salmon fillet either inoculated with S. baltica or P. fluorescen maintained remained a relatively low level of total volatile basic nitrogen (TVBN) (below 30 mg N/100 g during 8-days storage) and delayed increase of low total viable bacteria counts (TVC) with a longer lag phase of 2 days.

Epileptic Seizure Detection Based on Bidirectional Gated Recurrent Unit Network.

Visual inspection of long-term electroencephalography (EEG) is a tedious task for physicians in neurology. Based on bidirectional gated recurrent unit (Bi-GRU) neural network, an automatic seizure detection method is proposed in this paper to facilitate the diagnosis and treatment of epilepsy. Firstly, wavelet transforms are applied to EEG recordings for filtering pre-processing. Then the relative energies of signals in several particular frequency bands are calculated and inputted into Bi-GRU network. Afterwards, the outputs of Bi-GRU network are further processed by moving average filtering, threshold comparison and seizure merging to generate the discriminant results that the tested EEG belong to seizure or not. Evaluated on CHB-MIT scalp EEG database, the proposed seizure detection method obtained an average sensitivity of 93.89% and an average specificity of 98.49%. 124 out of 128 seizures were correctly detected and the achieved average false detection rate was 0.31 per hour on 867.14 h testing data. The results show the superiority of Bi-GRU network in seizure detection and the proposed detection method has a promising potential in the monitoring of long-term EEG.

Ornithine Decarboxylation System of Shewanella baltica Regulates Putrescine Production and Acid Resistance.

ABSTRACT: Shewanella baltica, one of the dominant spoilers of seafoods, can synthesize putrescine from ornithine under acidic conditions, which could result in food spoilage and health problems. We identified three regulatory enzymes (SpeC, SpeF, and PotE) in the ornithine decarboxylation (ODC) pathway of S. baltica by searching the NCBI database and exploring their functional roles through gene knock-out technology. The ornithine decarboxylase SpeC is an auxiliary adjustor of the ODC system, whereas the ornithine-putrescine transporter SpeE and ornithine decarboxylase SpeF participate in the production of extracellular putrescine. Exogenous addition of ornithine and putrescine promotes the extracellular secretion of putrescine by upregulating the expression of speF and potE. The putrescine biosynthesis and alkalization of cytoplasm is enhanced at weak acidic pH compared with neutral pH, especially at pH 6.0. The maximum upregulation of ODC genes and the optimum decarboxylation activity of SpeF are achieved in a weak acidic environment (pH 6.0), suggesting that the ODC pathway plays an important role in putrescine production and the cytoplasmic acid counteraction of S. baltica. This study contributes to a wider understanding of spoilage mechanisms in food systems and provides theoretical support for developing novel seafood preservation methods.

Roughness-Length-Based Characteristic Analysis of Intracranial EEG and Epileptic Seizure Prediction.

To identify precursors of epileptic seizures, an EEG characteristic analysis is carried out based on a roughness-length method, where fractal dimensions and intercept values are extracted to measure the structure complexity and the amplitude roughness of EEG signals in different phases. Using the significant changes of the fractal dimension and intercept in the preictal phase with respect to those in the interictal phase, a patient-specific seizure prediction algorithm is then proposed by combining with a gradient boosting classifier. The probabilistic outputs of the trained gradient boosting classifier are further processed by threshold comparison and rule-based judgment to distinguish preictal EEG from interictal EEG and to generate seizure alerts. The prediction algorithm was evaluated on 20 patients' intracranial EEG recordings from the Freiburg EEG database, which contains the preictal periods of 65 seizures and 499[Formula: see text]h interictal EEG. Setting the seizure prediction horizon as 2[Formula: see text]min, averaged sensitivity values of 90.42% and 91.67% with averaged false prediction rates of 0.12/h and 0.10/h were achieved for seizure occurrence periods of 30 and 50[Formula: see text]min, respectively. These results demonstrate the ability of fractal dimension and intercept metrics in predicting the occurrence of seizures.

Dynamic fabrication of microfluidic systems for particles separation based on optical projection lithography.

Microfluidic systems are widely used for applications in biology, medicine and chemistry. Particles separation by microfluidics is a scientific subject that requires ongoing research efforts. In this article, we demonstrate a micropillar-based particles separator fabricated using digital micromirror device (DMD)-based optical projection lithography from the perspectives of theory, design, simulation and experiments. Micropillars can be fabricated with customized shapes and sizes which shows high flexible and efficient. The particles separator employs the physical separation of a cylindrical array, a rectangular array, or a triangular array to separate particles. The simulation and experiment results indicate that the device with different micropillars could achieve separation of 20 and 200 µm polystyrene microspheres. Furthermore, the separation efficiency depended on flow rate and the shape of micropillars. All the results can be used to support the redesign of microfluidic structures to address particles separation needs.

4D Printing: A Review on Recent Progresses.

Since the late 1980s, additive manufacturing (AM), commonly known as three-dimensional (3D) printing, has been gradually popularized. However, the microstructures fabricated using 3D printing is static. To overcome this challenge, four-dimensional (4D) printing which defined as fabricating a complex spontaneous structure that changes with time respond in an intended manner to external stimuli. 4D printing originates in 3D printing, but beyond 3D printing. Although 4D printing is mainly based on 3D printing and become an branch of additive manufacturing, the fabricated objects are no longer static and can be transformed into complex structures by changing the size, shape, property and functionality under external stimuli, which makes 3D printing alive. Herein, recent major progresses in 4D printing are reviewed, including AM technologies for 4D printing, stimulation method, materials and applications. In addition, the current challenges and future prospects of 4D printing were highlighted.