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This paper proposes a fast coordinated power control method based on two augmented channels (AC) in battery energy storage system (BESS) to improve inertial and voltage support capability, i.e., a frequency-reactive power channel (FRPC) and a voltage-real power channel (VRPC). For frequency control in the power distribution system with high resistance/inductance ratio, the coupling mechanism between rate of change of frequency (RoCoF) and required reactive power (RRP) of grids is analyzed, indicating RoCoF is proportional to RRP. Thus, RoCoF is utilized in FRPC to generate reactive power for complementary inertial emulating control. Meanwhile, for voltage control, coupling characteristics between rate of change of voltage (RoCoV) and demanding real power (DRP) of grids is also studied, revealing RoCoV is proportional to DRP. Therefore, it can be adopted in VRPC to generate real power for complementary voltage control. Then, grid-voltage-modulated direct power control is selected as the inner power control loop to track power references with faster dynamic performance compared with traditional vector-oriented control. Finally, simulations and hardware-in-loop experiments validate improvement in performance of grid frequency and voltage control based on the proposed method.

Abstract Phase contrast x-ray imaging (PCXI) provides high-contrast images of weakly-attenuating structures like the lungs. PCXI, when paired with 4D X-ray Velocimetry (XV), can measure regional lung function and non-invasively assess the efficacy of emerging therapeutics. Bacteriophage therapy is an emerging antimicrobial treatment option for lung diseases such as cystic fibrosis (CF), particularly with increasing rates of multi-drug-resistant infections. Current efficacy assessment in animal models is highly invasive, typically requiring histological assessment. We aim to use XV techniques as non-invasive alternatives to demonstrate efficacy of bacteriophage therapy for treating Pseudomonas aeruginosa CF lung infections, measuring functional changes post-treatment. Time-resolved in vivo PCXI-CT scans of control, Pseudomonas-infected, and phage-treated mouse lungs were taken at the Australian Synchrotron Imaging and Medical Beamline. Using XV we measured local lung expansion and ventilation throughout the breath cycle, analysing the skew of the lung expansion distribution. CT images allowed visualisation of the projected air volume in the lungs, assessing structural lung damage. XV analysis demonstrated changes in lung expansion between infection and control groups, however there were no statistically significant differences between treated and placebo groups. In some cases where structural changes were not evident in the CT scans, XV successfully detected changes in lung function.

This short communication analyzes the power coupling mechanism of synchronous reference frame-based vector control (SRF-VC) of voltage source inverter (VSI), which is caused by the variation of voltage angle difference (VVAD) between voltage at point of common coupling (PCC) and grid voltage. Then, a power closed loop transfer function model is proposed to study the power coupling characteristics. It reveals that when there is an increase of output real power, the VSI will absorb coupling reactive power from power grids which will limit its real power transfer capability and even cause transient instability. Next, a power decoupling strategy for SRF-VC is proposed based on a dynamic feedforward power compensation (DFPC) algorithm, and its power decoupling capability is analyzed based on the transfer function. Simulations and experimental results show that the proposed method can not only reduce power coupling magnitudes in transient stage, but also realize power ripple cancellation in quasi-steady state.

The hybrid of female white crucian carp (Carassius auratus cuvieri, WCC) × male red crucian carp (Carassius auratus red var. RCC) (WR), combines desirable characteristics of both parents, including tender meat, rapid growth rate, and strong resistance. To test the hypoxia tolerance of WR, an experiment of exposure to hypoxic conditions was conducted on WR, RCC, and WCC. The results showed that WR and RCC exhibited stronger hypoxia tolerance capacity compared to WCC. The strong resistance to hypoxia of WR and RCC was manifested by the absence of damage to the hepatopancreas after hypoxia, and the fish can adapt to the hypoxic environment by enhancing the hematopoietic function of hematopoietic tissue, remodeling gill morphology, and activating the antioxidant system. By contrast, after hypoxia, the number of red blood cells and the concentration of hemoglobin in the blood of WCC decreased, and the hepatopancreas was seriously damaged, indicating that the WCC is not as tolerant to low oxygen conditions as RCC and WR.

Although long-distance international travel contributes significantly to global emissions from the transport sector, disaggregated travel demand forecasting models on long-distance international travel are scarce. Large infrastructure investments such as high-speed rail may have a profound impact on long-distance international travel demand and thus need to be evaluated using such models. In this study, a disaggregated travel demand forecasting model is estimated using Swedish national travel survey data from 2011-2016 along with detailed supply data from European road, train, and ferry networks and a World-wide air network, aiming at forecasting Swedes’ long-distance travel abroad. Mode choice, destination choice and trip generation are modelled by traditional Nested Logit models and Multinomial Logit models. The model is segmented by purpose (private or business) and for private trips also by number of nights away. The model estimation results reveal effects of individual socio-economic attributes, level-of-service attributes, and destination characteristics. Marginal effect estimates of level-of-service attributes for train suggest that infrastructure investments in high-speed rail network may have a profound effect on demand for long-distance international travel, especially for business trips.

Abstract The disaster caused by landslide is huge. To prevent the spread of the disaster to the maximum extent, it is particularly important to carry out landslide disaster treatment work. The selection of landslide disaster treatment alternative is a large scale group decision-making (LSGDM) problem. Because of the wide application of social media, a large number of experts and the public can participate in decision-making process, which is conducive to improving the efficiency and correctness of decision-making. A IF-TW-LSGDM method based on three-way decision (TWD) and intuitionistic fuzzy set (IFS) is proposed and applied to the selection of landslide treatment alternatives. First of all, considering that experts and the public participate in the evaluation of LSGDM events, respectively, the method of obtaining and handling the public evaluation information is given, and the information fusion approach of the public and experts evaluation information is given. Second, evaluation values represented by fuzzy numbers are converted into intuitionistic fuzzy numbers (IFNs), and the intuitionistic fuzzy evaluation decision matrix described by IFNs is obtained. Then, a new LSGDM method of alternatives classification and ranking based on IFS and TWD is proposed, the calculation steps and algorithm description are given. In this process, we first cluster the experts, then consider the identification and management of non-cooperative behavior of expert groups. This work provides an effective method based on LSGDM for the selection of landslide treatment alternatives. Finally, the sensitivity of parameters is analyzed, and the feasibility and effectiveness of this method are compared and verified.

This paper proposes a novel Multivariate Quotient-Difference (MQD) method to obtain the approximate analytical solution for AC power flow equations. Therefore, in the online environment, the power flow solutions covering different operating conditions can be directly obtained by plugging values into multiple symbolic variables, such that the power injections and consumptions of selected buses or areas can be independently adjusted. This method first derives a power flow solution through a Multivariate Power Series (MPS). Next, the MQD method is applied to transform the obtained MPS to a Multivariate Padé Approximants (MPA) to expand the Radius of Convergence (ROC), so that the accuracy of the derived analytical solution can be significantly increased. In addition, the hypersurface of the voltage stability boundary can be identified by an analytical formula obtained from the coefficients of MPA. This direct method for power flow solutions and voltage stability boundaries is fast for many online applications, since such analytical solutions can be derived offline and evaluated online by only plugging values into the symbolic variables according to the actual operating conditions. The proposed method is validated in detail on New England 39-bus and IEEE 118-bus systems with independent load variations in multi-regions.

Grid frequency dynamic is dominant by synchronous generators (SGs), but it is more and more obviously affected the voltage-source-converter-based (VSC-based) devices. This paper presents a modelling method of the real equivalent inertia of the VSynC-based VSC and an analysis approach for grid frequency dynamics. In this paper, the virtual synchronous control (VSynC)-based VSC is taken as an example. Firstly, grid frequency dynamic is introduced with and without considering energy constraints and cascaded control of the VSynC-based VSC, respectively. Then the swing equation model is established to study the real inertial characteristic of the VSynC-based VSC, which poses main effect on grid frequency dynamics. Based on the swing equation model, the real equivalent inertia characteristic is deduced under the consideration of the energy constraints and cascaded control dynamics of DC voltage control, and it is recognized as a transfer function, rather than the constant value like traditional SGs. Moreover, under the effect of the transfer-function-based inertia of the VSynC-based VSC, the bode-diagram-based analysis method is proposed in this paper to discuss the frequency dynamics of the power system with both SGs and VSynC-based VSCs. The zero-crossing frequency and phase margin in bode diagrams are used to evaluate the major characteristics of grid frequency, i.e. the rate of change of frequency (ROCOF) and nadir (the max deviation). Finally, case studies are implemented based on New England 39 Bus System to validate the correctness and effectiveness of the proposed modelling and analysis method.

Abstract Aging can be defined as a decline of physiological function that is more difficult to reverse, characterized by the loss of the physiological integrity of tissues, organs, and cells of an organism over time. Normal aging is associated with structural and functional changes in the brain, involving neuronal apoptosis, synaptic structure, neurotransmission, and metabolism alterations, leading to impairment in sleep, cognitive functions, memory, learning, and motor and sensory systems. Histone modification is a significant aging‐related epigenetic change that influences synaptic and mitochondrial function and immune and stress responses in the brain. This review discusses the changes in histone modifications that occur during brain aging, specifically methylation and acetylation, and the associated changes in gene transcription and protein expression. We observed that genes related to synaptic and mitochondrial function are downregulated in the aging brain, while genes related to immune response and inflammatory functions are upregulated.

Abstract Background Excessive extracellular matrix deposition and increased stiffness are typical features of solid tumors such as hepatocellular carcinoma (HCC) and pancreatic ductal adenocarcinoma (PDAC). These conditions create confined spaces for tumor cell migration and metastasis. The regulatory mechanism of confined migration remains unclear. Methods LC–MS was applied to determine the differentially expressed proteins between HCC tissues and corresponding adjacent tissue. Collective migration and single cell migration microfluidic devices with 6 μm-high confined channels were designed and fabricated to mimic the in vivo confined space. 3D invasion assay was created by Matrigel and Collagen I mixture treat to adherent cells. 3D spheroid formation under various stiffness environment was developed by different substitution percentage GelMA. Immunoprecipitation was performed to pull down the LH1-binding proteins, which were identified by LC–MS. Immunofluorescent staining, FRET, RT-PCR, Western blotting, FRAP, CCK-8, transwell cell migration, wound healing, orthotopic liver injection mouse model and in vivo imaging were used to evaluate the target expression and cellular phenotype. Results Lysyl hydroxylase 1 (LH1) promoted the confined migration of cancer cells at both collective and single cell levels. In addition, LH1 enhanced cell invasion in a 3D biomimetic model and spheroid formation in stiffer environments. High LH1 expression correlated with poor prognosis of both HCC and PDAC patients, while it also promoted in vivo metastasis. Mechanistically, LH1 bound and stabilized Septin2 (SEPT2) to enhance actin polymerization, depending on the hydroxylase domain. Finally, the subpopulation with high expression of both LH1 and SEPT2 had the poorest prognosis. Conclusions LH1 promotes the confined migration and metastasis of cancer cells by stabilizing SEPT2 and thus facilitating actin polymerization.

BackgroundEmerging evidence has indicated that remnant cholesterol (RC) could predict cardiovascular disease (CVD) incidence. Nevertheless, the relationship between RC and CVD risk, especially within the general Chinese population, remains scarce.ObjectiveThe present research aimed to assess whether RC concentrations and CVD outcomes in general Chinese adults are related.MethodsThe Cox proportional hazard model was established to explore the relationship between RC and the outcomes of CVD and CVD subgroups. A restricted cubic spline (RCS) was utilized to investigate the dose–response connection between RC and the risk of CVD outcomes, and the ROC curve was used to calculate the corresponding cutoff values. Moreover, stratified analysis was conducted to investigate the potential effect modification in the association between RC and CVD outcomes.ResultsSignificant positive associations were found between elevated categorical RC and increased risk of CVD (HR Q4, 1.80; 95% CI 1.15–2.79; P-value = 0.008), atherosclerotic cardiovascular disease (HR Q4, 2.00; 95% CI 1.22–3.27; P-value = 0.007), stroke (HR Q4, 1.66; 95% CI 1.02–2.69; P-value = 0.040), and ischemic stroke (HR Q4, 1.87, 95% CI 1.08–3.25; P-value = 0.034), respectively. Our study suggested that the incidence of CVD outcomes increased when RC levels were above 0.75 mmol/L. Importantly, the CVD risks related to RC were more likely to be those found in subjects aged above 60 years, women, subjects with BMI

Wind power forecast is becoming more and more important as the ever-increasing penetration of renewable energies brings uncertainties to the power systems. Although the numerical weather prediction (NWP) has already been widely applied on wind power forecast, it involves high computational burden with complex meteorological models, which has great uncertainty in real environment, so machine learning methods are the significant supplement for accurate wind power forecast. This paper proposes a deep learning model to improve the prediction accuracy based on the NWP data. Variational Mode Decomposition (VMD) is applied to extract time-series information. Furthermore, an encoder–decoder structure consisting of a dual attention-long short term memory (LSTM) neural network is constructed to enhance the forecasting accuracy. The comparison between the proposed model and several benchmark models, show the superiority of proposed model in effectively enhancing the prediction performance.

Abstract Severe harmonics propagation in power systems may result in increased power losses and equipment damages. In this paper, an elliptic formula is derived to analyse the harmonic spatial distribution not only at the substations but also along the power lines or cables and to give a system‐wide overview of harmonic levels. It is observed that harmonic distortion along power lines can be higher than that at the busbars and the maximum amplitude of harmonic voltage and current denoted as weak positions along power lines depends on the steady‐state harmonic angle difference of voltage and current at busbars, the length of power lines, and the harmonic order. All cases are modelled in detail by analytical geometry and analysed in MATLAB. In this regard, a method to identify the weak positions in terms of maximum harmonic levels in a power system is presented, and its corresponding harmonic orders are determined. The accuracy of the model is tested using time‐domain simulations in PSCAD/EMTDC.

Abstract Background The noradrenergic neurons of locus coeruleus (LC) project to the spinal dorsal horn (SDH), and release norepinephrine (NE) to inhibit pain transmission. However, its effect on pathological pain and the cellular mechanism in the SDH remains unclear. This study aimed to explore the analgesic effects and the anti-neuroinflammation mechanism of LC-spinal cord noradrenergic pathway (LC:SC) in neuropathic pain (NP) mice with sciatic chronic constriction injury. Methods The Designer Receptors Exclusively Activated by Designer Drugs (DREADD) was used to selectively activate LC:SC. Noradrenergic neuron-specific retro–adeno-associated virus was injected to the spinal cord. Pain threshold, LC and wide dynamic range (WDR) neuron firing, neuroinflammation (microglia and astrocyte activation, cytokine expression), and α2AR expression in SDH were evaluated. Results Activation of LC:SC with DREADD increased the mechanical and thermal nociceptive thresholds and reduced the WDR neuron firing. LC:SC activation (daily, 7 days) downregulated TNF-α and IL-1β expression, upregulated IL-4 and IL-10 expression in SDH, and inhibited microglia and astrocytes activation in NP mice. Immunofluorescence double staining confirmed that LC:SC activation decreased the expression of cytokines in microglia of the SDH. In addition, the effects of LC:SC activation could be reversed by intrathecal injection of yohimbine. Immunofluorescence of SDH showed that NE receptor α2B-AR was highly expressed in microglia in CCI mice. Conclusion These findings indicate that selective activation of LC:SC alleviates NP in mice by increasing the release of NE and reducing neuroinflammation of astrocytes and microglia in SDH.

Abstract Background COVID-19 has spread rapidly around the world, affecting a large percentage of the population. When lifting certain mandatory measures for an economic restart, robust surveillance must be established and implemented, with nucleic acid detection for SARS-CoV-2 as an essential component. Methods We tried to develop a one-tube detection platform based on RT-RPA (Reverse Transcription and Recombinase Polymerase Isothermal Amplification) and DNA Endonuclease-Targeted CRISPR Trans Reporter (DETECTR) technology, termed OR-DETECTR, to detect SARS-CoV-2. We designed RT-RPA primers of the RdRp and N genes following the SARS-CoV-2 gene sequence. We optimized reaction components so that the detection process could be carried out in one tube. Specificity was demonstrated by detecting nucleic acid samples from pseudoviruses from seven human coronaviruses and Influenza A (H1N1). Clinical samples were used to validate the platform and all results were compared to rRT-PCR. RNA standards and pseudoviruses diluted by different gradients were used to demonstrate the detection limit. Additionally, we have developed a lateral flow assay based on OR-DETECTR for detecting COVID-19. Results The OR-DETECTR detection process can be completed in one tube, which takes approximately 50 min. This method can specifically detect SARS-CoV-2 from seven human coronaviruses and Influenza A (H1N1), with a low detection limit of 2.5 copies/µl input (RNA standard) and 1 copy/µl input (pseudovirus). Results of six samples from SARS-CoV-2 patients, eight samples from patients with fever but no SARS-CoV-2 infection, and one mixed sample from 40 negative controls showed that OR-DETECTR is 100% consistent with rRT-PCR. The lateral flow assay based on OR-DETECTR can be used for the detection of COVID-19, and the detection limit is 2.5 copies/µl input. Conclusions The OR-DETECTR platform for the detection of COVID-19 is rapid, accurate, tube closed, easy-to-operate, and free of large instruments.

Non-Intrusive Load Monitoring (NILM) is particularly important for demand response. This paper proposes an innovative method based on a deep learning model to recognize the working state of electrical appliances using low frequency load data. The approach includes a data processing step, a deep learning model and a new accuracy calculation method. The data processing step consists of a multi-feature and high-dimensional method (MFHDM) and a pre-training process. The deep learning model consists of a convolutional neural network (CNN), a long-term short-term memory network (LSTM) and a random-forest (RF) algorithm. The proposed method addresses the label correlation problem and the class-imbalance problem. To test the proposed method, the Reference Energy Disaggregation Dataset (REDD) and the Pecan Street dataset (PSD) are used. A comparative analysis with several models shows that the proposed method can effectively improve electrical appliance recognition accuracy and realize NILM.

This paper proposes an analytical model for the modular multilevel converter (MMC) based on the theory of harmonic balance, which removes the iteration process for traditional models. The proposed model considers dynamic harmonic interactions between the modulation of converters and passive elements in the MMC. By transferring the equations into frequency-domain as complex Fourier series, a steady-state harmonic model is created with singular coefficients matrix. Then, through the elimination of all DC components in dynamic model, the singular coefficient matrix can be derived to nonsingular one, and the order of it can be reduced. Finally, the typical open-loop analytical model with DC neutral grounded MMC is derived aim, and the time-domain simulations is used to validate the effectiveness of proposed model. The proposed model can be used to accelerate the simulation and analyze the influence of parameters to guide the design of MMC.

Abstract Pancreatic cancer is one of the main causes of tumor-related deaths worldwide because of its low morbidity but extremely high mortality, and is therefore colloquially known as the “king of cancer.” Sudden onset and lack of early diagnostic biomarkers directly contribute to the extremely high mortality rate of pancreatic cancer patients, and also make it indistinguishable from benign pancreatic diseases and precancerous pancreatic lesions. Additionally, the lack of effective prognostic biomarkers makes it difficult for clinicians to formulate precise follow-up strategies based on the postoperative characteristics of the patients, which results in missed early diagnosis of recurrent pancreatic cancer. Long non-coding RNAs (lncRNAs) can influence cell proliferation, invasion/migration, apoptosis, and even chemoresistance via regulation of various signaling pathways, leading to pro- or anti-cancer outcomes. Given the versatile effects of lncRNAs on tumor progression, using a single lncRNA or combination of several lncRNAs may be an effective method for tumor diagnosis and prognostic predictions. This review will give a comprehensive overview of the most recent research related to lncRNAs in pancreatic cancer progression, as targeted therapies, and as biomarkers for the diagnosis and prognosis of pancreatic cancer.

Abstract Cancer remains one of the major culprits causing disease-related deaths and leads to a high morbidity and similar mortality. Insidious onset, difficult early detection and a lack of broad-spectrum and effective multi-cancer therapeutic targets have limited the prolongation of cancer patients’ survival for decades. Therefore, a versatile therapeutic target which is involved in various cancer-related signaling pathways and different cancers may be more effective for cancer targeted therapy. USP4, one of the DUBs members which participates in deubiquitination, an inverse process of ubiquitination, can regulate various classical cancer-related signaling pathways, and thereby plays a vital role in some pathological and physiological processes including tumor initiation and progression. Recently, USP4 has been found to exert versatile influences on cells proliferation, migration and invasion, also apoptosis of various tumors. Moreover, USP4 can also act as a prognostic biomarker in several cancers. This review will give a comprehensive introduction of USP4 about its regulatory mechanisms, related signaling pathways, pathophysiological functions and the roles in various cancers which may help us better understand its biological functions and improve future studies to construct suitable USP4-targeted cancer therapy system.

Pancreatic cancer is a highly malignant tumor with a poor survival prognosis. We attempted to establish a robust prognostic model to elucidate the clinicopathological association between lncRNA, which may lead to poor prognosis by influencing m6A modification, and pancreatic cancer. We investigated the lncRNAs expression level and the prognostic value in 440 PDAC patients and 171 normal tissues from GTEx, TCGA, and ICGC databases. The bioinformatic analysis and statistical analysis were used to illustrate the relationship. We implemented Pearson correlation analysis to explore the m6A-related lncRNAs, univariate Cox regression and Kaplan-Meier methods were performed to identify the seven prognostic lncRNAs signatures. We inputted them in the LASSO Cox regression to establish a prognostic model in the TCGA database, verified in the ICGC database. The AUC of the ROC curve of the training set is 0.887, while the validation set is 0.711. Each patient has calculated a risk score and divided it into low-risk and high-risk subgroups by the median value. Moreover, the model showed a robust prognostic ability in the stratification analysis of different risk subgroups, pathological grades, and recurrence events. We established a ceRNA network between lncRNAs and m6A regulators. Enrichment analysis indicated that malignancy-associated biological function and signaling pathways were enriched in the high-risk subgroup and m6A-related lncRNAs target mRNA. We have even identified small molecule drugs, such as Thapsigargin, Mepacrine, and Ellipticine, that may affect pancreatic cancer progression. We found that seven lncRNAs were highly expressed in tumor patients in the GTEx-TCGA database, and LncRNA CASC19/UCA1/LINC01094/LINC02323 were confirmed in both pancreatic cell lines and FISH relative quantity. We provided a comprehensive aerial view between m6A-related lncRNAs and pancreatic cancer’s clinicopathological characteristics, and performed experiments to verify the robustness of the prognostic model.

The role of the dopaminergic pathway in general anesthesia and its potential mechanisms are still unknown. In this study, we usedc-Fos staining combined with calcium fiber photometry recording to explore the activity of ventral tegmental area (VTA) dopaminergic neurons(VTA-DA) and nucleus accumbens (NAc) neurons during sevoflurane anesthesia. A genetically encoded dopamine (DA) sensor was used to investigate thefunction of the NAc in sevoflurane anesthesia. Chemogenetics and optogenetics were used to explore the role of the VTA-DA in sevofluraneanesthesia. Electroencephalogram (EEG) spectra, time of loss of righting reflex (LORR) and recovery of righting reflex (RORR) were recorded asassessment indicators. We found that VTA-DA and NAc neurons were inhibited during the induction period and were activated during the recoveryperiod of sevoflurane anesthesia. The fluorescence signals of dopamine decreased in the induction of and increased in the emergence from sevoflurane anesthesia.Activation of VTA-DA and the VTADA-NAc pathway delayed the induction and facilitated the emergence accompanying with thereduction of delta band and the augmentation of the gamma band. These data demonstrate that VTA-DA neurons play a critical role in modulating sevofluraneanesthesia via the VTADA-NAc pathway.

A popular and widely used combination therapy of leflunomide (LEF) and Tripterygium glycosides tablets (TGTS) has become a valuable clinical tool in China for the treatment of rheumatoid arthritis. This regimen has not been evaluated either in terms of interaction or toxicity, even given the rising concerns about LEF’s prolonged elimination half-life and TGT’s narrow therapeutic index, in addition to the current trend of using high doses of LEF. Thus, this study determines the potential adverse drug reactions between these two medicines. Reliable validated LC-MS/MS methods were used for the determination of teriflunomide (TER, the only active metabolite of LEF), and the main components of TGT: wilforlide A, wilforgine, wilfortrine, wilfordine, and wilforine. The results obtained from this investigation, as paralleled with the control groups, revealed that the Cmax and AUC0-t of TER were significantly decreased with separate co-administration, as the Cmax and AUC0-t were 30.17 ± 1.55 μg/mL and 24.47 ± 2.50 μg/mL, 374.55 ± 15.54 μg h/mL and 336.94 ± 21.19 μg h/mL, respectively (p < 0.05). Meanwhile, the pharmacokinetic profiles of the main components of TGT have also been affected by separate co-administration in rats. Therefore, herb–drug interactions between LEF and TGT have been proven.

Since their introduction in the 1840s, one of the largest mysteries of modern anesthesia are how general anesthetics create the state of reversible loss of consciousness. Increasing researchers have shown that neural pathways that regulate endogenous sleep–wake systems are also involved in general anesthesia. Recently, the Lateral Habenula (LHb) was considered as a hot spot for both natural sleep–wake and propofol-induced sedation; however, the role of the LHb and related pathways in the isoflurane-induced unconsciousness has yet to be identified. Here, using real-time calcium fiber photometry recordings in vivo, we found that isoflurane reversibly increased the activity of LHb glutamatergic neurons. Then, we selectively ablated LHb glutamatergic neurons in Vglut2-cre mice, which caused a longer induction time and less recovery time along with a decrease in delta-band power in mice under isoflurane anesthesia. Furthermore, using a chemogenetic approach to specifically activate LHb glutamatergic neurons shortened the induction time and prolonged the recovery time in mice under isoflurane anesthesia with an increase in delta-band power. In contrast, chemogenetic inhibition of LHb glutamatergic neurons was very similar to the effects of selective lesions of LHb glutamatergic neurons. Finally, optogenetic activation of LHb glutamatergic neurons or the synaptic terminals of LHb glutamatergic neurons in the rostromedial tegmental nucleus (RMTg) produced a hypnosis-promoting effect in isoflurane anesthesia with an increase in slow wave activity. Our results suggest that LHb glutamatergic neurons and pathway are vital in modulating isoflurane anesthesia.

Propofol is a worldwide-used intravenous general anesthetic with ideal effects, but hedonic effects of propofol have been reported and cause addictive issue. There is little known about the neurobiological mechanism of hedonic effects of propofol. Increasing researches have shown that the dopaminergic nervous system of the ventral tegmental area (VTA) and the noradrenergic system of locus coeruleus (LC) play a crucial role in hedonic experiences, which are putative sites for mediating the hedonic effects of propofol. In the present study, rat hedonic response scale and place conditioning paradigm were employed to examine the euphoric effects of propofol. In vivo GCaMP-based (AVV-hSyn-GCaMP6s) fiber photometry calcium imaging was used to monitor the real-time neuronal activity in VTA and LC area in rats exhibiting propofol-induced euphoric behaviors. Then DREADDs (designer receptors exclusively activated by designer drugs) modulation using rAAV-hSyn-hM4D(Gi)-EGFP was performed to confirm the neuronal substrate that mediates the euphoric effects of propofol. The score of hedonic facial responses was significantly increased in the 4 mg/kg group compared with that of the 0 mg/kg group. The locomotor activity in the propofol-paired compartment was significantly increased at the 4 mg/kg dose compared with that of the saline-paired group. When compared with the 0 mg/kg group, the place preference increased in the 4 mg/kg group. Administration of 4 mg/kg of propofol triggers reliable increases in GcaMP fluorescence. However, in the VTA GcaMP-expressing rats, administration of 4 mg/kg of propofol did not induce any change of GcaMP signals. The facial score and the place preference, which increased by 4 mg/kg propofol were abolished by chemogenetic inhibition of the neuronal activity in the LC area. Our results suggest that LC noradrenergic neurons, not VTA dopaminergic neurons, are directly involved in the hedonic effects of sub-anesthetic dose of propofol.

Pancreatic ductal adenocarcinoma (PDAC) is a malignancy with one of the worst prognoses worldwide and has an overall 5-year survival rate of only 9%. Although chemotherapy is the recommended treatment for patients with advanced PDAC, its efficacy is not satisfactory. The dense dysplastic stroma of PDAC is a major obstacle to the delivery of chemotherapy drugs and plays an important role in the progression of PDAC. Therefore, stroma-targeting therapy is considered a potential treatment strategy to improve the efficacy of chemotherapy and patient survival. While several preclinical studies have shown encouraging results, the anti-tumor potential of the PDAC stroma has also been revealed, and the extreme depletion might promote tumor progression and undermine patient survival. Therefore, achieving a balance between stromal abundance and depletion might be the further of stroma-targeting therapy. This review summarized the current progress of stroma-targeting therapy in PDAC and discussed the double-edged sword of its therapeutic effects.

Background: Pancreatic ductal adenocarcinoma (PDAC) leads to the majority of cancer-related deaths due to its morbidity with similar mortality. Lack of effective prognostic biomarkers are the main reason for belated post-operative intervention of recurrence which causes high mortality. Numerous systematic reviews and meta-analyses have explored the prognostic value of biomarkers in PDAC so far. In this article, we performed an umbrella review analyzing these studies to provide an overview of associations between prognostic biomarkers and PDAC survival outcome and synthesized these results to guide better clinical practice.Methods: Systematic reviews and meta-analyses investigating the associations between PDAC survival outcomes and prognostic biomarkers were acquired via the PubMed and Embase databases from inception till February 1, 2020. Associations supported by nominally statistically significant results were classified into strong, highly suggestive, suggestive, and weak based on several critical factors such as the statistical significance of summary estimates, the number of events, the estimate of the largest study included, interstudy heterogeneity, small-study effects, 95% predictive interval (PI), excess significance bias, and the results of credibility ceiling sensitivity analyses.Results: We included 41 meta-analyses containing 63 associations between PDAC survival outcomes and prognostic biomarkers. Although, none was supported by strong evidence among these associations, an association between C-reactive protein to albumin ratio (CAR) and PDAC overall survival (OS) and an association between neutrophil-lymphocyte ratio (NLR) and PDAC OS were supported by highly suggestive evidence. Otherwise, the association between lactate dehydrogenase (LDH) and PDAC OS was supported by suggestive evidence. The remaining 60 associations were supported by weak or not suggestive evidence.Conclusion: Associations between CAR or NLR and PDAC OS were supported by highly suggestive evidence. And the association between LDH and PDAC OS was supported by suggestive evidence. Although the methodological quality of the included systematic reviews and meta-analyses which were evaluated by AMSTAR2.0 is generally poor, the identification of the relatively robust prognostic biomarkers of PDAC may guide better post-operative intervention and follow-up to prolong patients' survival.

Electrical synapses between neurons exhibit a high degree of plasticity, which makes critical contributions to neuronal communication. The GABAergic parvalbumin-expressing (PV+) neurons in the thalamic reticular nucleus (TRN) interact with each other through electrical and chemical synapses. Plasticity of electrical synaptic transmission in TRN plays a key role in regulating thalamocortical and corticothalamic circuits and even the formation of consciousness. We here examined the effects of propofol, a commonly used general anesthetic agent, on the strength of electrical synapses between TRN PV+ neurons by fluorescence-guided patch-clamp recording and pharmacological methods. Results show that 100 μM propofol reduced the electrical synaptic strength between TRN PV+ neurons. Notably, the propofol-induced depression of electrical synaptic strength between TRN PV+ neurons was diminished by saclofen (10 μM, antagonist of GABAB receptors), but not blocked by gabazine (10 μM, antagonist of GABAA receptors). Application of baclofen (10 μM, agonist of GABAB receptors), similar to propofol, also reduced the electrical synaptic strength between TRN PV+ neurons. Moreover, the propofol-induced depression of electrical synaptic strength between TRN PV+ neurons was abolished by 9-CPA (100 μM, specific adenylyl cyclase inhibitor), and by KT5720 (1 μM, selective inhibitor of PKA). Our findings indicate that propofol acts on metabotropic GABAB receptors, resulting in a depression of electrical synaptic transmission of coupled TRN PV+ neurons, which is mediated by the adenylyl cyclase-cAMP-PKA signaling pathway. Our findings also imply that propofol may change the thalamocortical communication via inducing depression of electrical synaptic strength in the TRN.

Infections caused by multidrug-resistant (MDR) bacteria have highlighted the importance of the development of new antimicrobial agents. While bacteriophages (phages) are widely studied as alternative agents to antibiotics, combined treatments using phages and antibiotics have exhibited Phage–Antibiotic Synergy (PAS), in which antibiotics promote phage replication and extraordinary antimicrobial efficacy with reduced development of bacterial resistance. This review paper on the current progress of phage–antibiotic therapy includes aspects of the mechanisms of PAS and the therapeutic performance of PAS in combating multidrug-resistant bacterial infections. The choice of phages and antibiotics, the administration time and sequence, and the concentrations of the two agents impact the bacterial inhibitory effects to different extents.

Abstract In this paper, a battery energy storage system (BESS) based control method is proposed to improve the damping ratio of a target oscillation mode to a desired level by charging or discharging the installed BESS using local measurements. The expected damping improvement by BESS is derived analytically for both a single-machine-infinite-bus system and a multi-machine system. This BESS-based approach is tested on a four-generator, two-area power system. Effects of the power converter limit, response time delay, power system stabilizers and battery state-of-charge on the control performance are also investigated. Simulation results validate the effectiveness of the proposed approach.

This paper proposes a novel method for power system dynamic simulation that solves power system differential algebraic equations by a semi-analytical and semi-numerical approach using continued fractions. The method implements a two-stage scheme to enhance online performance of simulation: the offline derivation stage finds approximate analytical solutions, so-called “semi-analytical solutions,”for state variables of dynamic devices, such as generators in the form of power series of time with symbolic coefficients about system conditions; the online evaluation stage substitutes values on actual system conditions for symbolic coefficients, then transforms the solution into a continued fraction to prolong its time interval of accuracy, and finally calculates the system's trajectory over consecutive, adaptive time intervals for expected simulation results. A priori error bound for continued fractions is proposed to enable the simulation on adaptive time intervals. Compared with the conventional numerical simulation methods, the proposed continued fraction-based method has a fast simulation speed and a good suitability for parallel computing. The method is demonstrated and tested on the IEEE 9-bus system, the IEEE 39-bus system, and Polish 327-generator 2383-bus system.

Abstract Purpose Using a three-week household activity-travel survey, this paper explores the relationship between individuals’ self-reported physical, mental and social health conditions and their time allocation for different types of in-home and out-of-home time activities. Methods A path model is developed to investigate the roles of activity-travel time use on the self-reported health conditions, while the socio-demographics and residential environment characteristics are also considered. Results The model results reveal heterogeneous impacts of different types of activities and intensities on individual’s self-reported health conditions. This study, however, did not find evidence of positive relationship between cycling and walking and self-reported physical health condition, which has been found in many developed countries. Presumably this is because in developing countries like Indonesia the individuals who walk and cycle are likely to be a part of economically disadvantaged groups who have less awareness to their own health conditions. Conclusion Beside activity and travel time use factors, age and working status were found significantly affecting the self-reported health conditions, regardless of respondents’ gender and income. Neighbourhood characteristics, such as population density, are also found positively correlated to self-reported respondents’ physical, social and mental health conditions.

BackgroundAstrocytes are now considered as crucial modulators of neuronal synaptic transmission. General anesthetics have been found to inhibit astrocytic activities, but it is not clear whether general anesthetics within the clinical concentration range affects the astrocyte-mediated synaptic regulation.MethodsThe effects of propofol, dexmedetomidine, and ketamine within clinically effective ranges on the slow inward currents (SICs) were tested by using the whole-cell recording in acute prefrontal cortex (PFC) slice preparations of rats. Astrocytes culture and HPLC were used to measure the effects of different anesthetics on the glutamate release of astrocytes.ResultsPropofol and dexmedetomidine showed no significant effect on the amplitude or frequency of SICs. Ketamine was found to inhibit the frequency of SICs in a concentration-dependent manner. The SICs synchronization rate of paired neurons was inhibited by 30 μM ketamine (from 42.5 ± 1.4% to 9.6 ± 0.8%) and was abolished by 300 μM ketamine. The astrocytic glutamate release induced by DHPG, an agonist of astrocytic type I metabotropic glutamate receptors, was not affected by ketamine, and ifenprodil, a selective antagonist of GluN1/GluN2B receptor, blocked all SICs and enhanced the inhibitory effect of 30 μM ketamine on the frequency of SICs. Ketamine at low concentration (3 μM) could inhibit the frequency of SICs, not the miniature excitatory postsynaptic currents (mEPSCs), and the inhibition rate of SICs was significantly higher than mEPSCs with 30 μM ketamine (44.5 ± 3% inhibition vs. 28.3 ± 6% inhibition).ConclusionOur data indicated that ketamine, not propofol and dexmedetomidine, within clinical concentration range inhibits glutamatergic transmission from astrocytes to neurons, which is likely mediated by the extrasynaptic GluN1/GluN2B receptor activation.

It is well-known that ac power flows of a power system do not have a closed-form analytical solution in general. This paper proposes a multi-dimensional holomorphic embedding method that derives analytical multivariate power series to approach true power flow solutions. This method embeds multiple independent variables into power flow equations and hence, can, respectively, scale power injections or consumptions of selected buses or groups of buses. Then, via a physical germ solution, the method can represent each bus voltage as a multivariate power series about symbolic variables on the system condition so as to derive approximate analytical power flow solutions. This method has a non-iterative mechanism unlike the traditional numerical methods for power flow calculation. Its solution can be derived offline and then evaluated in real time by plugging values into symbolic variables according to the actual condition, so the method fits better into online applications, such as voltage stability assessment. The method is first illustrated in detail on a 4-bus power system and then demonstrated on the IEEE 14-bus power system considering independent load variations in four regions.

With the increasing integration of renewable energy resources and other forms of dispersed generation, more and more variances and uncertainties are brought to modern power systems. The dynamic security assessment (DSA) of modern power systems is facing challenges in ensuring its accuracy for unpredictable operating conditions (OC). This paper proposes a novel approach that uses random forest (RF) for online DSA. Hourly scenarios are generated for the database according to the forecast errors of renewable energy resources, which are calculated from historical data. Fed with online measurement data, it is able to not only predict the security states of current OC with high accuracy, but also indicate the confidence level of the security states one minute ahead of the real time by an outlier identification method. The results of RF together with outlier identification show high accuracy in the presence of variances and uncertainties due to wind power generation. The performance of this approach is verified on the operational model of western Danish power system with around 200 transmission lines and 400 buses.

Although long-distance international travel contributes significantly to global emissions from the transport sector, disaggregated travel demand forecasting models on long-distance international travel are scarce. Large infrastructure investments such as high-speed rail may have a profound impact on longdistance international travel demand and thus need to be evaluated using such models. In this study, a disaggregated travel demand forecasting model is estimated using Swedish national travel survey data from 2011-2016 along with detailed supply data from European road, train, and ferry networks and a World-wide air network, aiming at forecasting Swedes' long-distance travel abroad. Mode choice, destination choice and trip generation are modelled by traditional Nested Logit models and Multinomial Logit models. The model is segmented by purpose (private or business) and for private trips also by number of nights away. The model estimation results reveal effects of individual socioeconomic attributes, level-of-service attributes, and destination characteristics. Marginal effect estimates of level-of-service attributes for train suggest that infrastructure investments in highspeed rail network may have a profound effect on demand for long-distance international travel, especially for business trips. [ABSTRACT FROM AUTHOR]

This article discusses a rare case of trans-anal barotrauma in a 25-year-old man who was shot in the anus with an air gun. The patient experienced symptoms of abdominal distension and pain, and imaging revealed air in the abdomen, chest, and scrotum. The patient underwent laparoscopic exploration and loop ileostomy, and had a successful recovery. The article emphasizes the importance of prompt diagnosis and treatment for this condition, as well as the need for education and training for users of high-pressure air equipment. The document is a systematic review of laparoscopic appendicectomy in obese patients, conducted by Dasari BVM, Baker J, Markar S, and Gardiner K and published in the International Journal of Surgery in 2015. The review examines the clinical outcomes of this surgical procedure and concludes that it leads to improvements in patient outcomes. This review provides valuable information for researchers and medical professionals interested in the topic. [Extracted from the article]