13C-labeling reveals how membrane lipid components contribute to triacylglycerol accumulation in Chlamydomonas.

Lipid metabolism in microalgae has attracted much interest due to potential utilization of lipids as feedstocks for biofuels, nutraceuticals, and other high-value compounds. Chlamydomonas reinhardtii is a model organism for characterizing the synthesis of the neutral lipid triacylglycerol (TAG), from which biodiesel is made. While much of TAG accumulation under N-deprivation is the result of de novo fatty acid (FA) synthesis, recent work has revealed that approximately one-third of FAs, especially polyunsaturated FAs (PUFAs), come from preexisting membrane lipids. Here, we used 13C-isotopic labeling and mass spectrometry to analyze the turnover of glycerol backbones, headgroups, FAs, whole molecules, and molecular fragments of individual lipids. About one-third of the glyceryl backbones in TAG are derived from preexisting membrane lipids, as are approximately one-third of FAs. The different moieties of the major galactolipids turn over synchronously, while the FAs of diacylglyceryltrimethylhomoserine (DGTS), the most abundant extraplastidial lipid, turn over independently of the rest of the molecule. The major plastidic lipid monogalactosyldiacylglycerol (MGDG), whose predominant species is 18:3α/16:4, was previously shown to be a major source of PUFAs for TAG synthesis. This study reveals that MGDG turns over as whole molecules, the 18:3α/16:4 species is present in both DAG and TAG, and the positional distribution of these PUFAs is identical in MGDG, DAG, and TAG. We conclude that headgroup removal with subsequent acylation is the mechanism by which the major MGDG species is converted to TAG during N-deprivation. This has noteworthy implications for engineering the composition of microalgal TAG for food, fuel, and other applications.

Research on a Time Difference Processing Method for RTD-Fluxgate Data Based on the Combination of the Mahalanobis Distance and Group Covariance.

During the measurement of magnetic fields, Residence Time Difference (RTD)-fluxgate sensors suffer from abnormal time difference jumps due to the random interference of magnetic core noise and environmental noise, which results in gross errors. This situation restricts the improvement of sensor accuracy and stability. In order to solve the above problems efficiently, a time difference gross error processing method based on the combination of the Mahalanobis distance (MD) and group covariance is presented in this paper, and the processing effects of different methods are compared and analyzed. The results of the simulation and experiment indicate that the proposed method is more advantageous in identifying the gross error in time difference. The signal-to-noise ratio for the time difference is improved by about 34 times, while the fluctuation of the Negative Magnetic Saturation Time (NMST) ΔTNMST is reduced by 95.402%, which significantly reduces the fluctuation of time difference and effectively improves the accuracy and stability of the sensor.

Recycling of Nutrients from Dairy Wastewater by Extremophilic Microalgae with High Ammonia Tolerance.

This study explored the possibility of incorporating extremophilic algal cultivation into dairy wastewater treatment by characterizing a unique algal strain. Results showed that extremophilic microalgae Chlorella vulgaris CA1 newly isolated from dairy wastewater tolerated a high level of ammonia nitrogen (2.7 g/L), which was over 20 times the ammonia nitrogen that regular Chlorella sp. could tolerate. The isolate was mixotrophically cultured in dairy effluent treated by anaerobic digestion (AD) for recycling nutrients and polishing the wastewater. The highest biomass content of 13.3 g/L and protein content of 43.4% were achieved in the culture in AD effluent. Up to 96% of the total nitrogen and 79% of the total phosphorus were removed from the dairy AD effluent. The ability of the algae to tolerate a high level of ammonia nitrogen suggests the potential for direct nutrient recycling from dairy wastewater while producing algal biomass and high value bioproducts.

A High Stability Time Difference Readout Technique of RTD-Fluxgate Sensors.

The performance of Residence Times Difference (RTD)-fluxgate sensors is closely related to the time difference readout technique. The noise of the induction signal affects the quality of the output signal of the following circuit and the time difference detection, so the stability of the sensor is limited. Based on the analysis of the uncertainty of the RTD-fluxgate using the Bidirectional Magnetic Saturation Time Difference (BMSTD) readout scheme, the relationship between the saturation state of the magnetic core and the target (DC) magnetic field is studied in this article. It is proposed that combining the excitation and induction signals can provide the Negative Magnetic Saturation Time (NMST), which is a detection quantity used to measure the target magnetic field. Also, a mathematical model of output response between NMST and the target magnetic field is established, which analyzes the output NMST and sensitivity of the RTD-fluxgate sensor under different excitation conditions and is compared to the BMSTD readout scheme. The experiment results indicate that this technique can effectively reduce the noise influence. The fluctuation of time difference is less than ±0.1 µs in a target magnetic field range of ±5 × 104 nT. The accuracy and stability of the sensor are improved, so the RTD-fluxgate using the readout technique of high stability time difference is suitable for detecting weak magnetic fields.

[Study of neuronal spike-frequency adaptation with transcranial magneto-acoustical stimulation].

Transcranial magneto-acoustical stimulation (TMAS), utilizing focused ultrasound and a magnetostatic field to generate an electric current in tissue fluid to regulate the activities of neurons, has high spatial resolution and penetration depth. The neuronal spike-frequency adaptation plays an important role in the treatment of neural information. In this paper, we study the effects of ultrasonic intensity, magnetostatic field intensity and ultrasonic frequency on the neuronal spike-frequency adaptation based on the Ermentrout neuron model. The simulation results show that, the peak time interval becomes smaller, the interspike interval becomes shorter and the time of the firing of the neuron is shortened with the increasing of the magnetostatic field intensity. With the increase of the adaptive variables, the initial spike-frequency is shifted to the right with the magnetostatic field intensity, and the spike-frequency is linearly related to the increase of the magnetostatic field intensity in steady state. The simulation effect with change of the ultrasonic intensity is consistent with the change of magnetostatic field intensity. The change of the ultrasonic frequency has no effect on the neuronal spike-frequency adaptation. Under the different adaptive variables, with the increase of the adaptive variables, the initial spike-frequency amplitude decreased with the increasing of the ultrasonic frequency, and the spike-frequency is linearly related to the increase of the ultrasonic frequency in steady state. These results of the study can help us to reveal the mechanism of transcranial magneto-acoustical stimulation on the neuronal spike-frequency adaptation, and provide a theoretical basis for its application in the treatment of neurological disorders.

Overexpression of the Phosphatidylcholine:DiacylglycerolCholinephosphotransferase (PDCT) gene increases carbon flux toward triacylglycerol (TAG) synthesis in Camelinasativa seeds.

Camelinasativa has considerable promise as a dedicated industrial oilseed crop. Its oil-based blends have been tested and approved as liquid transportation fuels. Previously, we utilized metabolomic and transcriptomic profiling approaches and identified metabolic bottlenecks that control oil production and accumulation in seeds. Accordingly, we selected candidate genes for the metabolic engineering of Camelina. Here we targeted the overexpression of Camelina PDCT gene, which encodes the phosphatidylcholine: diacylglycerol cholinephosphotransferase enzyme. PDCT is proposed as a gatekeeper responsible for the interconversions of diacylglycerol (DAG) and phosphatidylcholine (PC) pools and has the potential to increase the levels of TAG in seeds. To confirm whether increased CsPDCT activity in developing Camelina seeds would enhance carbon flux toward increased levels of TAG and alter oil composition, we overexpressed the CsPDCT gene under the control of the seed-specific phaseolin promoter. Camelina transgenics exhibited significant increases in seed yield (19-56%), seed oil content (9-13%), oil yields per plant (32-76%), and altered polyunsaturated fatty acid (PUFA) content compared to their parental wild-type (WT) plants. Results from [14C] acetate labeling of Camelina developing embryos expressing CsPDCT in culture indicated increased rates of radiolabeled fatty acid incorporation into glycerolipids (up to 64%, 59%, and 43% higher in TAG, DAG, and PC, respectively), relative to WT embryos. We conclude that overexpression of PDCT appears to be a positive strategy to achieve a synergistic effect on the flux through the TAG synthesis pathway, thereby further increasing oil yields in Camelina.

Research on the dynamic hysteresis loop model of the residence times difference (RTD)-fluxgate.

Based on the core hysteresis features, the RTD-fluxgate core, while working, is repeatedly saturated with excitation field. When the fluxgate simulates, the accurate characteristic model of the core may provide a precise simulation result. As the shape of the ideal hysteresis loop model is fixed, it cannot accurately reflect the actual dynamic changing rules of the hysteresis loop. In order to improve the fluxgate simulation accuracy, a dynamic hysteresis loop model containing the parameters which have actual physical meanings is proposed based on the changing rule of the permeability parameter when the fluxgate is working. Compared with the ideal hysteresis loop model, this model has considered the dynamic features of the hysteresis loop, which makes the simulation results closer to the actual output. In addition, other hysteresis loops of different magnetic materials can be explained utilizing the described model for an example of amorphous magnetic material in this manuscript. The model has been validated by the output response comparison between experiment results and fitting results using the model.

Nonlinear neural networks adaptive control for a class of fractional-order tuberculosis model.

The problem of nonlinear adaptive control for a class of fractional-order tuberculosis (TB) model is studied in this paper. By analyzing the transmission mechanism of TB and the characteristics of fractional calculus, a fractional-order TB dynamical model is established with media coverage and treatment as control variables. With the help of universal approximation principle of radial basis function neural networks and the positive invariant set of established TB model, the expressions of control variables are designed and the stability of error model is analyzed. Thus, the adaptive control method can guarantee that the number of susceptible and infected individuals can be kept close to the corresponding control targets. Finally, the designed control variables are illustrated by numerical examples. The results indicate that the proposed adaptive controllers can effectively control the established TB model and ensure the stability of controlled model, and two control measures can protect more people from tuberculosis infection.

Central Aortic Blood Pressure Waveform Estimation with a Temporal Convolutional Network.

A novel temporal convolutional network (TCN) model is utilized to reconstruct the central aortic blood pressure (aBP) waveform from the radial blood pressure waveform. The method does not need manual feature extraction as traditional transfer function approaches. The data acquired by the SphygmoCor CVMS device in 1,032 participants as a measured database and a public database of 4,374 virtual healthy subjects were used to compare the accuracy and computational cost of the TCN model with the published convolutional neural network and bi-directional long short-term memory (CNN-BiLSTM) model. The TCN model was compared with CNN-BiLSTM in the root mean square error (RMSE). The TCN model generally outperformed the existing CNN-BiLSTM model in terms of accuracy and computational cost. For the measured and public databases, the RMSE of the waveform using the TCN model was 0.55 ± 0.40 mmHg and 0.84 ± 0.29 mmHg, respectively. The training time of the TCN model was 9.63 min and 25.51 min for the entire training set; the average test time was around 1.79 ms and 8.58 ms per test pulse signal from the measured and public databases, respectively. The TCN model is accurate and fast for processing long input signals, and provides a novel method for measuring the aBP waveform. This method may contribute to the early monitoring and prevention of cardiovascular disease.

Ultrasound deep brain stimulation decelerates telomere shortening in Alzheimer's disease and aging mice.

Telomere length is a reliable biomarker for health and longevity prediction in both humans and animals. The common neuromodulation techniques, including deep brain stimulation (DBS) and optogenetics, have excellent spatial resolution and depth penetration but require implementation of electrodes or optical fibers. Therefore, it is important to develop methods for noninvasive modulation of telomere length. Herein, we reported on a new method for decelerating telomere shortening using noninvasive ultrasound deep brain stimulation (UDBS). Firstly, we found that UDBS could activate the telomerase-associated proteins in normal mice. Then, in the Alzheimer's disease mice, UDBS was observed to decelerate telomere shortening of the cortex and myocardial tissue and to effectively improve spatial learning and memory abilities. Similarly, UDBS was found to significantly slow down telomere shortening of the cortex and peripheral blood, and improve motor and cognitive functions in aging mice. Finally, transcriptome analysis revealed that UDBS upregulated the neuroactive ligand-receptor interaction pathway. Overall, the present findings established the critical role of UDBS in delaying telomere shortening and indicated that ultrasound modulation of telomere length may constitute an effective therapeutic strategy for aging and aging-related diseases.

(E)-Isopentyl 3-(3,4-dihy-droxy-phen-yl)-acrylate.

The title compound, C(14)H(18)O(4), a derivative of caffeic acid, has an E configuration about the C=C bond. The benzene ring is almost coplanar with the C=C-C(O)-O-C linker [maximum deviation = 0.050 (2) Å], making a dihedral angle of only 4.53 (2)°. In the mol-ecule, the adjacent hy-droxy groups form an O-H⋯O inter-action. In the crystal, mol-ecules are linked by O-H⋯O hydrogen bonds, generating a chain propagating in the [110] direction.

Measuring the Evolution of Risk Communication Strategy for Health Authorities During the COVID-19 Pandemic: An Empirical Comparison Between China and the United States.

Objectives: Investigate how the speech context of news conferences reveals the risk communication strategies for health authorities during COVID-19 and measure the evolution of those risk communication strategies. Methods: We collected news conference transcripts concerning COVID-19 for the first quarter from the official websites of the Centers for Disease Control and Prevention (CDC) and the National Health Commission of the People's Republic of China (NHC) in 2020. Quantitative analyses were conducted on the topics and emotions of transcripts to measure the evolution of risk communication strategy. A total of three types of analysis were carried out in our study: topic, sentiment, and risk communication evolution analyses. Results: The trending topics and the number of these in the two institutions evolved with the infection status. The CDC and NHC maintained primarily neutral sentiment, while the non-neutral sentiment of the CDC swung more dramatically. Furthermore, the changing pattern of risk communication evolution for the CDC and NHC varied, where the latter had a more stable change routine. Conclusion: Our study finds that the strategies could be measured by topic variation, emotional expressions, and confirmed cases. The CDC and NHC tend to adopt different risk communication strategies and have specific change routines facing the pandemic. In addition, our findings contribute to addressing the WHO research agenda for managing risk communication during the COVID-19 pandemic, which helps health authorities formulate and measure risk communication strategies.

Rapid cell pairing and fusion based on oscillating bubbles within an acoustofluidic device.

Cell fusion is an essential event in many biological processes and has gained increasing attention in the field of biotechnology. In this study, we demonstrate an effective and convenient strategy for cell capture, pairing, and fusion based on oscillating bubbles within an acoustofluidic device. Multirectangular structures of the same size were fabricated at the sidewall of polydimethylsiloxane to generate monodisperse microbubbles. These microbubbles oscillated with a similar amplitude under single-frequency acoustic excitation. Cells were simultaneously captured and paired on the surface of the oscillating bubbles within 40 ms, and the efficiency reached approximately 90%. Homotypic or heterotypic cell membrane fusion was achieved within 15 and 20 min, respectively. More importantly, the homotypic fused cells enabled migration and proliferation at 24 h, indicating that the important biological functions were not altered.

Re-Programing Glucose Catabolism in the Microalga Chlorella sorokiniana under Light Condition.

The microalga Chlorella sorokiniana has attracted much attention for lipid production and wastewater treatment. It can perform photosynthesis and organic carbon utilization concurrently. To understand its phototrophic metabolism, a biomass compositional analysis, a 13C metabolic flux analysis, and metabolite pool size analyses were performed. Under dark condition, the oxidative pentose phosphate pathway (OPP) was the major route for glucose catabolism (88% carbon flux) and a cyclic OPP-glycolytic route for glucose catabolism was formed. Under light condition, fluxes in the glucose catabolism, tricarboxylic acid (TCA) cycle, and anaplerotic reaction (CO2 fixation via phosphoenolpyruvate carboxylase) were all suppressed. Meanwhile, the RuBisCO reaction became active and the ratio of its carbon fixation to glucose carbon utilization was determined as 7:100. Moreover, light condition significantly reduced the pool sizes of sugar phosphate metabolites (such as E4P, F6P, and S7P) and promoted biomass synthesis (which reached 0.155 h-1). In addition, light condition increased glucose consumption rates, leading to higher ATP and NADPH production and a higher protein content (43% vs. 30%) in the biomass during the exponential growth phase.

Fast identification and quantification of c-Fos protein using you-only-look-once-v5.

In neuroscience, protein activity characterizes neuronal excitability in response to a diverse array of external stimuli and represents the cell state throughout the development of brain diseases. Importantly, it is necessary to characterize the proteins involved in disease progression, nuclear function determination, stimulation method effect, and other aspects. Therefore, the quantification of protein activity is indispensable in neuroscience. Currently, ImageJ software and manual counting are two of the most commonly used methods to quantify proteins. To improve the efficiency of quantitative protein statistics, the you-only-look-once-v5 (YOLOv5) model was proposed. In this study, c-Fos immunofluorescence images data set as an example to verify the efficacy of the system using protein quantitative statistics. The results indicate that YOLOv5 was less time-consuming or obtained higher accuracy than other methods (time: ImageJ software: 80.12 ± 1.67 s, manual counting: 3.41 ± 0.25 s, YOLOv5: 0.0251 ± 0.0003 s, p < 0.0001, n = 83; simple linear regression equation: ImageJ software: Y = 1.013 × X + 0.776, R 2 = 0.837; manual counting: Y = 1.0*X + 0, R 2 = 1; YOLOv5: Y = 0.9730*X + 0.3821, R 2 = 0.933, n = 130). The findings suggest that the YOLOv5 algorithm provides feasible methods for quantitative statistical analysis of proteins and has good potential for application in detecting target proteins in neuroscience.

Ultrasound Deep Brain Stimulation Modulates Body Temperature in Mice.

Body temperature plays a critical role in rehabilitation, and numerous studies proved that the regulation of body temperature contributes to the sensorimotor recovery of patients with brain diseases such as stroke. The hypothalamus plays a key role in thermoregulation. Ultrasound deep brain stimulation (UDBS) can noninvasively modulate deep brain nuclei and have potential applications in the treatment of Parkinson's disease, Alzheimer's disease, and depression, among others. The purpose of this study was to investigate whether ultrasound stimulation of the hypothalamus could regulate body temperature in free-moving mice. Results showed that thermoregulation was related to ultrasonic parameters (pulse repetition frequency (PRF), duty cycle, total time, and acoustic pressure). UDBS of the preoptic area of the anterior hypothalamus at 500 Hz PRF could significantly reduce body temperature ( [Formula: see text] at t = 5 min, [Formula: see text] at t = 10 min, [Formula: see text] at t = 15 min). Meanwhile, UDBS of the dorsomedial hypothalamus at 10 Hz PRF triggered a significant increase in body temperature ( [Formula: see text] at t = 5 min, [Formula: see text] at t = 10 min). These results suggest that UDBS, as a noninvasive neuromodulation tool, may play a key role in the future clinical treatment of malignant hyperthermia and hypothermia.

Non-Cavitation Targeted Microbubble-Mediated Single-Cell Sonoporation.

Sonoporation employs ultrasound accompanied by microbubble (MB) cavitation to induce the reversible disruption of cell membranes and has been exploited as a promising intracellular macromolecular delivery strategy. Due to the damage to cells resulting from strong cavitation, it is difficult to balance efficient delivery and high survival rates. In this paper, a traveling surface acoustic wave (TSAW) device, consisting of a TSAW chip and a polydimethylsiloxane (PDMS) channel, was designed to explore single-cell sonoporation using targeted microbubbles (TMBs) in a non-cavitation regime. A TSAW was applied to precisely manipulate the movement of the TMBs attached to MDA-MB-231 cells, leading to sonoporation at a single-cell level. The impact of input voltage and the number of TMBs on cell sonoporation was investigated. In addition, the physical mechanisms of bubble cavitation or the acoustic radiation force (ARF) for cell sonoporation were analyzed. The TMBs excited by an ARF directly propelled cell membrane deformation, leading to reversible perforation in the cell membrane. When two TMBs adhered to the cell surface and the input voltage was 350 mVpp, the cell sonoporation efficiency went up to 83%.

Influence of Cr, Mn, Co and Ni Addition on Crystallization Behavior of Al13Fe4 Phase in Al-5Fe Alloys Based on ThermoDynamic Calculations.

Alloying is an effective method to refine coarse grains of an Al13Fe4 phase and strengthen Al-Fe alloys. However, the grain refinement mechanism remains unclear in terms of the thermodynamics. Herein, the influence of M-element, i.e., Cr, Mn, Co and Ni, addition on the activity of Al and Fe atoms, Gibbs free energy of the Al13Fe4 nucleus in Al-Fe melt and the formation enthalpy of an Al13Fe4 phase in Al-Fe alloys is systematically investigated using the extended Miedema model, Wilson equation, and first-principle calculations, respectively. The results reveal that the addition of different M elements increases the activity of Fe atoms and reduces the Gibbs free energy of the Al13Fe4 nucleus in Al-Fe melt, where the incorporation of Ni renders the most obvious effect, followed by Mn, Co, and Cr. Additionally, the formation enthalpy decreases in the following order: Al78(Fe23Cr) > Al78(Fe23Mn) > Al13Fe4 > Al78(Fe23Ni) > Al78(Fe23Co), where the formation enthalpy of Al78(Fe23Ni) is close to Al78(Fe23Co). Moreover, the presence of Ni promotes the nucleation of the Al13Fe4 phase in Al-Fe alloys, which reveals the mechanism of grain refinement from a thermodynamics viewpoint.

Closed-loop wearable ultrasound deep brain stimulation system based on EEG in mice.

Objective. Epilepsy is one of the most common severe brain disorders. Ultrasound deep brain stimulation (UDBS) has shown a potential capability to suppress seizures. However, because seizures occur sporadically, it is necessary to develop a closed-loop system to suppress them. Therefore, we developed a closed-loop wearable UDBS system that delivers ultrasound to the hippocampus to suppress epileptic seizures.Approach.Mice were intraperitoneally injected with 10 mg kg-1kainic acid and divided into sham and UDBS groups. Epileptic seizures were detected by applying both long short-term memory (LSTM) and bidirectional LSTM (BILSTM) networks according to EEG signal characteristics. When epileptic seizures were detected, the closed-loop UDBS system automatically activated a trigger switch to stimulate the hippocampus for 10 min and continuously record EEG signals until 20 min after ultrasonic stimulation. EEG signals were analyzed using the MATLAB software. After EEG recording, we observed the survival rate of the experimental mice for 72 h.Main results.The BiLSTM network was found to have preferable classification performance over the LSTM network. The closed-loop UDBS system with BiLSTM could automatically detect epileptic seizures using EEG signals and effectively reduce epileptic EEG power spectral density and seizure duration by 10.73%, eventually improving the survival rate of early epileptic mice from 67.57% in the sham group to 88.89% in the UDBS group.Significance.The closed-loop UDBS system developed in this study could be an effective clinical tool for the control of epilepsy.

Transcranial Ultrasound Stimulation Suppresses Neuroinflammation in a Chronic Mouse Model of Parkinson's Disease.

OBJECTIVE: Neuroinflammation contributes to the development and progression of Parkinson's disease (PD). The aim of this study was to examine whether ultrasound (US) stimulation of the subthalamic nucleus (STN) could suppress the neuroinflammation in a chronic PD mouse model induced by 1-Methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine (MPTP). METHODS: A chronic PD mouse model was built by injections of 20mg/kg MPTP and 250 mg/kg probenecid at 3.5-day intervals for 5 weeks. Mice were randomized into control+sham, MPTP+sham and MPTP+STN+US group. For MPTP+STN+US group, ultrasound wave (3.8 MHz, 50% duty cycle, 1 kHz pulse repetition frequency, 30 min/day) was delivered to the STN the day after MPTP and probenecid injection (the early stage of PD progression). The rotarod test and pole test were performed to evaluate the behavioral changes after ultrasound treatment. Then, the activity of microglia and astrocyte were measured to evaluate the inflammation level in the brain. RESULTS: Ultrasound stimulation improved the latency to falls in the rotarod test (p = 0.033) and decreased the climbing time in the pole test (p = 0.016) compared with MPTP+sham group. Moreover, ultrasound stimulation reduced the chronic inflammation response as shown in microglia (p = 0.007) and astrocyte (p = 0.032) activation. In addition, HE, Nissl and Tunel staining showed that no brain tissue injury was induced by US. CONCLUSION: These findings demonstrated that ultrasound stimulation could suppress neuroinflammation in PD mice. SIGNIFICANCE: Transcranial ultrasound neuromodulation offers a novel approach for Parkinson's disease intervention, potentially through its anti-neuroinflammation functions.