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Wound healing is a complicated obstacle, especially for chronic wounds. Mesenchymal stem cell-derived exosomes may be a promising cell-free approach for treating skin wound healing. Exosomes can accelerate wound healing by attenuating inflammation, promoting angiogenesis, cell proliferation, extracellular matrix production and remodeling. However, many issues, such as off-target effects and high degradation of exosomes in wound sites need to be addressed before applying into clinical therapy. Therefore, the bioengineering technology has been introduced to modify exosomes with greater stability and specific therapeutic property. To prolong the function time and the local concentration of exosomes in the wound bed, the use of biomaterials to load exosomes emerges as a promising strategy. In this review, we summarize the biogenesis and characteristics of exosomes, the role of exosomes in wound healing, and the therapeutic applications of modified-exosomes in wound healing. The challenges and prospects of exosomes in wound healing are also discussed.

P-glycoprotein (Pgp) overexpressed in blood brain barrier (BBB) is hypothesized to lower brain drug concentrations and thus inhibit anticonvulsant effects in drug-resistant epilepsy. Pluronic P85 (P85) was proved to enhance the delivery of drugs into the brain by inhibition of Pgp. To determine whether the surfactant P85 [versus Pgp inhibitor tariquidar (TQD)] enhance phenytoin (PHT) into the brain in drug-resistant rats with chronic mesial temporal lobe epilepsy (MTLE) induced by lithium-pilocarpine, in brain of which Pgp were overexpressed, then direct verification of PHT transport via measurement of PHT concentration in brain using microdialysis. The drug-resistant model rats were randomly divided into three groups, which were treated with PHT, 1%P85 + PHT, or PHT+TQD, respectively. 1%P85 + PHT treatment displayed a lower ratio of the area under the curve (AUC) of the PHT concentration in the brain/plasma even than that of the PHT treatment in model rats (p 0.05). For the ratio of the kidney/plasma, PHT+TQD treatment model group had the highest ratio of the other treatments in model rats. Thus, P85 oppositely decreased PHT concentration in brain in drug-resistant model rats with Pgp overexpressed MTLE while TQD could increase PHT distribution in brain.

A sensitive, convenient, rapid and economic liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed to determine cinacalcet concentration in human plasma. A stable isotope cinacalcet (cinacalcet-D3) was selected as internal standard and the analytes were extracted from plasma samples by a one-step precipitation procedure. Chromatography separation was conducted on an Eclipse Plus C18 column by gradient elution with mobile phase of methanol-water-ammonium formate system at a constant flow rate of 0.6 mL/min. Mass spectrometric detection was conducted by multiple reaction monitoring using positive electrospray ionization. Cinacalcet concentrations in human plasma were determined over the concentration range of 0.1–50 ng/mL. The accuracies of lower limit of quantification (LLOQ) and quality control samples were all within the range of 85–115%, and the inter- and intra-batch precisions (CV%) were all within 15%. The average extraction recovery rates were 95.67–102.88%, and the quantification was not interfered by the matrix components. The validated method was successfully applied to determined cinacalcet concentrations in human plasma from secondary hyperparathyroidism patients.

Introduction: Water, as an essential strategic resource, is diminishing; this has been framed as a financial risk. We aim to quantitively investigate the impact of water use and technology on the stock market and compare the differences in China and Japan, which represent emerging and mature markets, respectively.Method: We constructed three models using the difference generalized method of moments. The first and second models focused on how water use could influence stock market volatility and returns; the third model added technology as an interaction to explore its impact on the above mechanism. We used an ARIMA-EGARCH model to predict the trend of marginal stock market return with an increase in industrial water use in the next 5 years.Results and Discussion: The results show that 1) water use increases the stock market volatility in both countries, but Japan shows a greater increase than China; 2) water use has a negative impact on stock market returns in China and a positive impact in Japan; 3) technology plays a positive role in the second model, while the ARIMA-EGARCH results correspond to the first two conclusions, which verifies the reasonability of the models. We conclude that heterogeneity exists in the two different market types because of technology level.

Context Ferroptosis was described as an important contributor to the myocardial ischaemia/reperfusion (MIR) injury, and britanin (Bri) was reported to exert antitumor and anti-inflammatory activities. Objective Our study explores the effect and mechanism of Bri on MIR damage. Materials and methods The rat model of MIR was established by ligation of the left anterior descending coronary artery. Male Sprague–Dawley (SD) rats were divided into three groups: sham group (n = 6), MIR group (n = 6) and MIR + Bri group (n = 6; 50 mg/kg). Rats were intragastrically pre-treated with Bri or normal saline once daily for 3 days. To further verify the role and mechanism of Bri, H9C2 cells were subjected to hypoxia plus reoxygenation (H/R) to induce the in vitro model of MIR. Results Compared with MIR rats, Bri significantly decreased infarct area (22.50% vs. 38.67%), myocardial apoptosis (23.00% vs. 41.5%), creatine phosphokinase (0.57 U/mL vs. 0.76 U/mL), and lactate dehydrogenase levels (3.18 U/mL vs. 5.17 U/mL), concomitant with alleviation of ferroptosis. Mechanistically, Bri treatment induced the activation of the adenosine monophosphate activated protein kinase (AMPK)/glycogen synthase kinase 3β (GSK3β)/nuclear factor erythroid 2-related factor 2 (Nrf2) pathway in vivo. In addition, the AMPK/GSK3β/Nrf2 pathway participated in the regulation of glutathione peroxidase 4 (GPX4) expression, and silencing of Nrf2 attenuated the effect of Bri on H/R-induced cell injury. Discussion and conclusions Bri protected against ferroptosis-mediated MIR damage by upregulating GPX4 through activation of the AMPK/GSK3β/Nrf2 signalling, suggesting that Bri might become a novel therapeutic agent for MIR.

IntroductionSocial anxiety disorder (SAD) and autism spectrum disorder (ASD) are highly overlapping in symptoms and have a high rate of comorbidity, posing challenges in diagnosis and intervention for both disorders. Both disorders are linked to abnormal attention to the eyes, yet how they interactively modulate the attentional process to the eyes remains unclear.MethodsIn this study, we explored how autistic traits and social anxiety in college students separately and together affected different temporal stages of attention to the eyes. Participants were instructed to view virtual faces for 10 s and make an emotional judgment, while their eye movements were recorded.ResultsWe found that social anxiety and autistic traits affected different temporal stages of eye-looking. Social anxiety only affected the first fixation duration on the eyes, while autistic traits were associated with eye avoidance at several time points in the later stage. More importantly, we found an interactive effect of autistic traits and social anxiety on the initial attention to the eyes: Among people scoring high on autistic traits, social anxiety was related to an early avoidance of the eyes as well as attention maintenance once fixated on the eyes.DiscussionOur study suggests the separate and interactive roles of social anxiety and autistic traits in attention to the eyes. It contributes to a deeper understanding of the mechanisms of social attention in both SAD and ASD and highlights the application of psychiatric diagnoses using eye-tracking techniques.

Background: Alcohol use disorder (AUD) is characterized by chronic excessive alcohol consumption, often alternating with periods of abstinence known as alcohol withdrawal syndrome (AWS). Diazepam is the preferred benzodiazepine for treatment of alcohol withdrawal syndrome under most circumstances, but the specific mechanism underlying the treatment needs further research.Methods: We constructed an animal model of two-bottle choices and chronic intermittent ethanol exposure. LC-MS/MS proteomic analysis based on the label-free and intensity-based quantification approach was used to detect the protein profile of the whole brain. Weighted gene correlated network analysis was applied for scale-free network topology analysis. We established a protein–protein interaction network based on the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software and identified hub proteins by CytoHubba and MCODE plugins of Cytoscape. The online tool Targetscan identified miRNA–mRNA pair interactions.Results: Seven hub proteins (Dlg3, Dlg4, Shank3, Grin2b, Camk2b, Camk2a and Syngap1) were implicated in alcohol withdrawal syndrome or diazepam treatment. In enrichment analysis, glutamatergic synapses were considered the most important pathway related to alcohol use disorder. Decreased glutamatergic synapses were observed in the late stage of withdrawal, as a protective mechanism that attenuated withdrawal-induced excitotoxicity. Diazepam treatment during withdrawal increased glutamatergic synapses, alleviating withdrawal-induced synapse inhibition.Conclusion: Glutamatergic synapses are considered the most important pathway related to alcohol use disorder that may be a potential molecular target for new interventional strategies.

Dysfunction of potassium voltage-gated channel subfamily Q member 1 (KCNQ1) is a primary cause of long QT syndrome type 1 (LQT1). Here, we report a missense mutation P441L in KCNQ1 C-terminus of a 37-year-old woman with severe LQT1 phenotype. Variant P441L transporting to the plasma membrane and interacting with KCNE1 were both markedly decreased, leading to potassium efflux disorder and eventually LQT1. Mutations between the C-terminal helix A and helix B of KCNQ1 have linked with low cardiac event risk, however, we firstly find variant P441L causing a severe LQT1 phenotype with a high risk of cardiac events.

Objective: To establish a population pharmacokinetic model in Chinese psychiatric patients to characterize escitalopram pharmacokinetic profile to identify factors influencing drug exposure, and through simulation to compare the results with the established therapeutic reference range.Methods: Demographic information, dosing regimen, CYP2C19 genotype, concomitant medications, and liver and kidney function indicators were retrospectively collected for inpatients taking escitalopram with therapeutic drug monitoring from 2018 to 2021. Nonlinear mixed-effects modeling was used to model the pharmacokinetic characteristics of escitalopram. Goodness-of-fit plots, bootstrapping, and normalized prediction distribution errors were used to evaluate the model. Simulation for different dosing regimens was based on the final estimations.Results: The study comprised 106 patients and 337 measurements of serum sample. A structural model with one compartment with first-order absorption and elimination described the data adequately. The population-estimated apparent volume of distribution and apparent clearance were 815 and 16.3 L/h, respectively. Age and CYP2C19 phenotype had a significant effect on the apparent clearance (CL/F). CL/F of escitalopram decreased with increased age, and CL/F of poor metabolizer patients was significantly lower than in extensive and immediate metabolizer patients. The final model-based simulation showed that the daily dose of adolescents with poor metabolizer might be as high as 15 mg or 20 mg and referring to the therapeutic range for adults may result in overdose and a high risk of adverse effects in older patients.Conclusion: A population pharmacokinetics model of escitalopram was successfully created for the Chinese population. Depending on the age of the patients, CYP2C19 genotype and serum drug concentrations throughout treatment are required for adequate individualization of dosing regimens. When developing a regimen for older patients, especially those who are poor metabolizers, vigilance is required.

Abstract The pharmacokinetic variability of lamotrigine (LTG) plays a significant role in its dosing requirements. Our goal here was to use noninvasive clinical parameters to predict the dose-adjusted concentrations (C/D ratio) of LTG based on machine learning (ML) algorithms. A total of 1141 therapeutic drug-monitoring measurements were used, 80% of which were randomly selected as the "derivation cohort" to develop the prediction algorithm, and the remaining 20% constituted the "validation cohort" to test the finally selected model. Fifteen ML models were optimized and evaluated by tenfold cross-validation on the "derivation cohort,” and were filtered by the mean absolute error (MAE). On the whole, the nonlinear models outperformed the linear models. The extra-trees’ regression algorithm delivered good performance, and was chosen to establish the predictive model. The important features were then analyzed and parameters of the model adjusted to develop the best prediction model, which accurately described the C/D ratio of LTG, especially in the intermediate-to-high range (≥ 22.1 μg mL−1 g−1 day), as illustrated by a minimal bias (mean relative error (%) = + 3%), good precision (MAE = 8.7 μg mL−1 g−1 day), and a high percentage of predictions within ± 20% of the empirical values (60.47%). This is the first study, to the best of our knowledge, to use ML algorithms to predict the C/D ratio of LTG. The results here can help clinicians adjust doses of LTG administered to patients to minimize adverse reactions.

In order to study the nonlinear characteristics of self-excited aerodynamic forces of bluff body bridge section with the change of motion parameters, a numerical wind tunnel is established by the dynamic mesh technique of computational fluid dynamics (CFD). A state-by-state forced vibration method is used to identify the self-excited aerodynamic forces of single degree-of-freedom (DOF) heaving and pitching motion. Fast Fourier transform (FFT) is adopted to obtain frequency-domain data for analysis. The reliability of the obtained aerodynamic results is verified by wind tunnel tests. The results show that the high-order harmonic components are found in the self-excited aerodynamic forces of semiclosed box deck section, which are more significant in aerodynamic lift than in aerodynamic moment. The proportion of aerodynamic nonlinear components increases with amplitude. The effect of amplitude on the nonlinear components of heaving motion is generally higher than that of pitching motion, and aerodynamic moment is highly sensitive to the increase of vertical amplitude. The variation of the nonlinear components of the deck section with frequency is not a simple monotonic relationship, and there is a stationary point at 10 Hz frequency. The existence of wind attack angle makes the proportion of nonlinear components reach more than 30% and greatly increases the proportion of second harmonic. In addition, the high-order harmonic components, which are not integer multiples, are found at large amplitude and positive angle of attack.

Background: Emerging evidence implicates the dysregulated kynurenine pathway (KP), an immune-inflammatory pathway, in the pathophysiology of mood disorders (MD), including depression and bipolar disorder characterized by a low-grade chronic pro-inflammatory state. The metabolites of the KP, an important part of the microbiota-gut-brain axis, serve as immune system modulators linking the gut microbiota (GM) with the host central nervous system.Aim: This bibliometric analysis aimed to provide a first glimpse into the KP in MD, with a focus on GM research in this field, to guide future research and promote the development of this field.Methods: Publications relating to the KP in MD between the years 2000 and 2020 were retrieved from the Scopus and Web of Science Core Collection (WoSCC), and analyzed in CiteSpace (5.7 R5W), biblioshiny (using R-Studio), and VOSviewer (1.6.16).Results: In total, 1,064 and 948 documents were extracted from the Scopus and WoSCC databases, respectively. The publications have shown rapid growth since 2006, partly owing to the largest research hotspot appearing since then, “quinolinic acid.” All the top five most relevant journals were in the neuropsychiatry field, such as Brain Behavior and Immunity. The United States and Innsbruck Medical University were the most influential country and institute, respectively. Journal co-citation analysis showed a strong tendency toward co-citation of research in the psychiatry field. Reference co-citation analysis revealed that the top four most important research focuses were “kynurenine pathway,” “psychoneuroimmunology,” “indoleamine 2,3-dioxygenase,” and “proinflammatory cytokines,” and the most recent focus was “gut-brain axis,” thus indicating the role of the KP in bridging the GM and the host immune system, and together reflecting the field’s research foundations. Overlap analysis between the thematic map of keywords and the keyword burst analysis revealed that the topics “Alzheimer’s disease,” “prefrontal cortex,” and “acid,” were research frontiers.Conclusion: This comprehensive bibliometric study provides an updated perspective on research associated with the KP in MD, with a focus on the current status of GM research in this field. This perspective may benefit researchers in choosing suitable journals and collaborators, and aid in the further understanding of the field’s hotspots and frontiers, thus facilitating future research.

This paper explores the nonlinear characteristics of the self-excited aerodynamic forces of a semi-closed box deck section to perfect the theory of aeroelastic response analysis. A numerical wind tunnel model was established based on the computational fluid dynamics (CFD) method. The heaving-pitching coupled motion is realized by loading user-defined function (UDF) and dynamic grid technology. The self-excited aerodynamic forces varying with amplitude are identified and analyzed, and the reliability of the aerodynamic results obtained by numerical simulation is verified in the wind tunnel test. In the heaving-pitching coupled motion, the results show that the nonlinear characteristics of aerodynamic forces, especially the aerodynamic moment, are mainly affected by the pitching motion. The phenomenon of high-order harmonic energy transfer is observed with the increase in pitching amplitude, and the main component of high-order harmonic can be determined by the pitching amplitude. The contribution of heaving motion to aerodynamic forces nonlinear components is small, but its influence on nonlinear characteristics is complex. Small amplitude heaving motion plays a positive damping role in heaving-pitching coupled motion, and its scope and effect of positive damping action are affected by pitching motion. The extreme value heaving amplitude of positive damping action is observed in the aerodynamic lift.

Background: There is a crucial link between the gut microbiota and the host central nervous system, and the communication between them occurs via a bidirectional pathway termed the “microbiota-gut-brain axis.” The gut microbiome in the modern environment has markedly changed in response to environmental factors. These changes may affect a broad range of host psychiatric disorders, such as depression, by interacting with the host through metabolic, immune, neural, and endocrine pathways. Nevertheless, the general aspects of the links between the gut microbiota and depression have not been systematically investigated through bibliometric analysis.Aim: This study aimed to analyze the current status and developing trends in gut microbiota research in the depression field through bibliometric and visual analysis.Methods: A total of 1,962 publications published between 1999 and 2019 were retrieved from the Web of Science Core Collection. CiteSpace (5.6 R5) was used to perform collaboration network analysis, co-citation analysis, co-occurrence analysis, and citation burst detection.Results: The number of publications has been rapidly growing since 2010. The collaboration network analysis revealed that the USA, University College Cork, and John F. Cryan were the most influential country, institute, and scholar, respectively. The most productive and co-cited journals were Brain Behavior and Immunity and Proceedings of the National Academy of Sciences of the United States of America, respectively. The co-citation analysis of references revealed that the most recent research focus was in the largest theme cluster, “cytokines,” thus reflecting the important research foundation in this field. The co-occurrence analysis of keywords revealed that “fecal microbiota” and “microbiome” have become the top two research hotspots since 2013. The citation burst detection for keywords identified several keywords, including “Parkinson's disease,” “microbiota-gut-brain axis,” “microbiome,” “dysbiosis,” “bipolar disorder,” “impact,” “C reactive protein,” and “immune system,” as new research frontiers, which have currently ongoing bursts.Conclusions: These results provide an instructive perspective on the current research and future directions in the study of the links between the gut microbiota and depression, which may help researchers choose suitable cooperators or journals, and promote their research illustrating the underlying molecular mechanisms of depression, including its etiology, prevention, and treatment.

L-Asparagine (ASN) is the catalyze substrate of L-asparaginase (ASNase), which is an important drug for acute lymphoblastic leukemia (ALL) patients. The ASN level is found to be closely associated with the effectiveness of ASNase treatment. In this study, a hydrophilic interaction liquid chromatography tandem mass spectrometry (HILIC-MS/MS) method was developed for the determination of ASN in the human serum using a stable isotope-labeled internal standard (ASN-D3). Serum samples were prepared by a one-step precipitation procedure using methanol and separated by an Agilent HILIC Plus column with the mobile phase of methanol-water (95 : 5, v/v, containing 5 mM ammonium formate and 0.1% formic acid), at a constant flow rate of 0.3 mL/min. Mass spectrometric analysis was conducted using multiple-reaction monitoring in the positive electrospray ionization mode. Serum ASN concentrations were determined over a linear calibration curve range of 2–200 μM, with acceptable accuracies and precisions. The validated HILIC-MS/MS method was successfully applied to the quantification of ASN levels in the serum from patients with ALL. Collectively, the research may shed new light on an alternative rapid, simple, and convenient quantitative method for determination of serum ASN in ALL patients treated with ASNase.

BackgroundActigraphs are wrist-worn devices that record tri-axial accelerometry data used clinically and in research studies. The expense of research-grade actigraphs, however, limit their widespread adoption, especially in clinical settings. Tri-axial accelerometer-based consumer wearable devices have gained worldwide popularity and hold potential for a cost-effective alternative. The lack of independent validation of minute-to-minute accelerometer data with polysomnographic data or even research-grade actigraphs, as well as access to raw data has hindered the utility and acceptance of consumer-grade actigraphs.MethodsSleep clinic patients wore a consumer-grade wearable (Huami Arc) on their non-dominant wrist while undergoing an overnight polysomnography (PSG) study. The sample was split into two, 20 in a training group and 21 in a testing group. In addition to the Arc, the testing group also wore a research-grade actigraph (Philips Actiwatch Spectrum). Sleep was scored for each 60-s epoch on both devices using the Cole-Kripke algorithm.ResultsBased on analysis of our training group, Arc and PSG data were aligned best when a threshold of 10 units was used to examine the Arc data. Using this threshold value in our testing group, the Arc has an accuracy of 90.3%±4.3%, sleep sensitivity (or wake specificity) of 95.5%±3.5%, and sleep specificity (wake sensitivity) of 55.6%±22.7%. Compared to PSG, Actiwatch has an accuracy of 88.7%±4.5%, sleep sensitivity of 92.6%±5.2%, and sleep specificity of 60.5%±20.2%, comparable to that observed in the Arc.ConclusionsAn optimized sleep/wake threshold value was identified for a consumer-grade wearable Arc trained by PSG data. By applying this sleep/wake threshold value for Arc generated accelerometer data, when compared to PSG, sleep and wake estimates were adequate and comparable to those generated by a clinical-grade actigraph. As with other actigraphs, sleep specificity plateaus due to limitations in distinguishing wake without movement from sleep. Further studies are needed to evaluate the Arc's ability to differentiate between sleep and wake using other sources of data available from the Arc, such as high resolution accelerometry and photoplethysmography.

Abstract Background Actigraphs are widely used portable wrist-worn devices that record tri-axial accelerometry data. These data can be used to approximate amount and timing of sleep and wake. Their clinical utility is limited, however, by their expense. Tri-axial accelerometer-based consumer wearable devices (so-called fitness monitors) have gained popularity and could represent cost-effective research alternatives to more expensive devices. Lack of independent validation of minute-to-minute accelerometer data for consumer devices has hindered their utility and acceptance. Methods We studied a consumer-grade wearable device, Arc (Huami Inc., Mountain View CA), for which minute-to-minute accelerometer data (vector magnitude) could be obtained. Twelve healthy participants and 19 sleep clinic patients wore on their non-dominant wrist, both an Arc and a research-grade actigraph (Actiwatch Spectrum, Philips, Bend OR) continuously over a period of 48 h in free-living conditions. Time-stamped data from each participant were aligned and the Cole-Kripke algorithm was used to assign a state of “sleep” or “wake” for each minute-long epoch recorded by the Arc. The auto and low scoring settings on the Actiwatch software (Actiware) were used to determine sleep and wake from the Actiwatch data and were used as the comparators. Receiver operating characteristic curves were used to optimize the relationship between the devices. Results Minute-by-minute Arc and Actiwatch data were highly correlated (r = 0.94, Spearman correlation) over the 48-h study period. Treating the Actiwatch auto scoring as the gold standard for determination of sleep and wake, Arc has an overall accuracy of 99.0% ± 0.17% (SEM), a sensitivity of 99.4% ± 0.19%, and a specificity of 84.5% ± 1.9% for the determination of sleep. As compared to the Actiwatch low scoring, Arc has an overall accuracy of 95.2% ± 0.36%, a sensitivity of 95.7% ± 0.47%, and a specificity of 91.7% ± 0.60% for the determination of sleep. Conclusions The Arc, a consumer wearable device in which minute-by-minute activity data could be collected and compared, yielded fundamentally similar sleep scoring metrics as compared to a commonly used clinical-grade actigraph (Actiwatch). We found high degrees of agreement in minute-to-minute data scoring for sleep and wake periods between the two devices.

Information sampling can reduce uncertainty in future decisions but is often costly. To maximize reward, people need to balance sampling cost and information gain. Here we aimed to understand how autistic traits influence the optimality of information sampling and to identify the particularly affected cognitive processes. Healthy human adults with different levels of autistic traits performed a probabilistic inference task, where they could sequentially sample information to increase their likelihood of correct inference and may choose to stop at any moment. We manipulated the cost and evidence associated with each sample and compared participants' performance to strategies that maximize expected gain. We found that participants were overall close to optimal but also showed autistic-trait-related differences. Participants with higher autistic traits had a higher efficiency of winning rewards when the sampling cost was zero but a lower efficiency when the cost was high and the evidence was more ambiguous. Computational modeling of participants' sampling choices and decision times revealed a two-stage decision process, with the second stage being an optional second thought. Participants may consider cost in the first stage and evidence in the second stage, or in the reverse order. The probability of choosing to stop sampling at a specific stage increases with increasing cost or increasing evidence. Surprisingly, autistic traits did not influence the decision in either stage. However, participants with higher autistic traits inclined to consider cost first, while those with lower autistic traits considered cost or evidence first in a more balanced way. This would lead to the observed autistic-trait-related advantages or disadvantages in sampling optimality, depending on whether the optimal sampling strategy is determined only by cost or jointly by cost and evidence.

The purpose of this study was to compare the pharmacokinetic profiles of tetramethylpyrazine phosphate (TMPP) in plasma and extracellular fluid of the cerebral cortex of rats via three delivery routes: intranasal (i.n.), intragastric (i.g.) and intravenous (i.v.) administration. After i.n., i.g. and i.v. administration of a single-dose at 10 mg/kg, cerebral cortex dialysates and plasma samples drawn from the carotid artery were collected at timed intervals. The concentration of TMPP in the samples was analyzed by HPLC. The area under the concentration–time curve (AUC) and the ratio of the AUCbrain to the AUCplasma (drug targeting efficiency, DTE) was calculated to evaluate the brain targeting efficiency of the drug via these different routes of administration. After i.n. administration, TMPP was rapidly absorbed to reach its peak plasma concentration within 5 min and showed a delayed uptake into cerebral cortex (tmax=15 min). The ratio of the AUCbrain dialysates value between i.n. route and i.v. injection was 0.68, which was greater than that obtained after i.g. administration (0.43). The systemic bioavailability obtained with i.n. administration was greater than that obtained by the i.g. route (86.33% vs. 50.39%), whereas the DTE of the nasal route was 78.89%, close to that of oral administration (85.69%). These results indicate that TMPP is rapidly absorbed from the nasal mucosa into the systemic circulation, and then crosses the blood–brain barrier (BBB) to reach the cerebral cortex. Intranasal administration of TMPP could be a promising alternative to intravenous and oral approaches.

Metal additive manufacturing (MAM) is an emerging and disruptive technology that builds three-dimensional (3D) components by adding layer-upon-layer of metallic materials. The complex cyclic thermal history and highly localized energy can produce large temperature gradients, which will, in turn, lead to compressive and tensile stress during the MAM process and eventually result in residual stress. Being an issue of great concern, residual stress, which can cause distortion, delamination, cracking, etc., is considered a key mechanical quantity that affects the manufacturing quality and service performance of MAM parts. In this review paper, the ongoing work in the field of residual stress determination and control for MAM is described with a particular emphasis on the experimental measurement/control methods and numerical models. We also provide insight on what still requires to be achieved and the research opportunities and challenges.

Desmoplasia is a hallmark of intrahepatic cholangiocarcinoma (ICC), which constitutes a barrier to infiltration of lymphocyte, but not myeloid cells. Given that dense desmoplastic stroma has been reported to be a barrier to infiltration of lymphocyte, but not myeloid cells. We here investigated whether fibroblastic FAP influenced ICC progression via non-T cell-related immune mechanisms. We demonstrated fibroblastic FAP expression was critical for STAT3 activation and CCL2 production, and ICC-CAFs were the primary source of CCL2 in human ICC microenvironment by using ICC-Fbs from six ICC patients. Fibroblastic knockdown of FAP significantly impaired the ability of ICC-CAFs to promote ICC growth, MDSCs infiltration and angiogenesis, which was restored by adding exogenous CCL2. Furthermore, interestingly, the tumor-promoting effect of fibroblastic FAP is dependent on MDSCs via secretion of CCL2, as depletion of Gr-1+ cells reversed the restoring effects of exogenous CCL2 on tumor growth and angiogenesis. In vitro migration assay confirmed that exogenous CCL2 could rescue the impaired ability of ICC-Fbs to attract Gr-1+ cells caused by fibroblastic FAP knockdown. In contrast, fibroblastic FAP knockdown had no effect on ICC cell proliferation and apoptotic resistance. Depletion MDSCs by anti-Gr-1 monoclonal antibody in subcutaneous transplanted tumor model abrogated tumor promotion by ICC-CAFs suggested that the pro-tumor function of Fibroblastic FAP relied on MDSCs. Mechanical, flow cytometry and chamber migration assay were conducted to find Fibroblastic FAP was required by the ability of ICC-CAFs to promote MDSC migration directly. Moreover, fibroblastic FAP knockdown had no effect on cell proliferation and apoptotic resistance. Here, we revealed the T-cell independent mechanisms underlying the ICC-promoting effect of fibroblastic FAP by attracting MDSCs via CCL2, which was mainly attributed to the ability of FAP to attract MDSCs and suggests that specific targeting fibroblastic FAP may represent a promising therapeutic strategy against ICC.

Epigenetic alterations represent a sort of functional modifications related to the genome that are not responsible for changes in the nucleotide sequence. DNA methylation is one of such epigenetic modifications that have been studied intensively for the past several decades. The transfer of a methyl group to the 5 position of a cytosine is the key feature of DNA methylation. A simple change as such can be caused by a variety of factors, which can be the cause of many serious diseases including several neurodegenerative diseases. In this review, we have reviewed and summarized recent progress regarding DNA methylation in four major neurodegenerative diseases: Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. The studies of these four major neurodegenerative diseases conclude the strong suggestion of the important role DNA methylation plays in these diseases. However, each of these diseases has not yet been understood completely as details in some areas remain unclear, and will be investigated in future studies. We hope this review can provide new insights into the understanding of neurodegenerative diseases from the epigenetic perspective. [ABSTRACT FROM AUTHOR]

Lignin accounts for approximately 30% of the weight of herbaceous biomass. Utilizing lignin in asphalt pavement industry could enhance the performance of pavement while balancing the construction cost. This study aims to evaluate the feasibility of utilizing lignin as a bitumen performance improver. For this purpose, lignin derived from aspen wood chips (labeled as KL) and corn stalk residues (labeled as CL) were selected to prepare the lignin modified bituminous binder. The properties of the lignin modified binder were investigated through rheological, mechanical and chemical tests. The multiple stress creep recovery (MSCR) test results indicated that adding lignin decreased the Jnr of based binder by a range of 8% to 23% depending on the stress and lignin type. Lignin showed a positive effect on the low temperature performance of asphalt binder, because at −18 °C, KL and CL were able to reduce the stiffness of base binder from 441 MPa to 369 MPa and 378 MPa, respectively. However, lignin was found to deteriorate the fatigue life and workability of base binder up to 30% and 126%. With bituminous mixture, application of lignin modifiers improved the Marshall Stability and moisture resistance of base mixture up to 21% and 13%, respectively. Although, adding lignin modifiers decreased the molecular weight of asphalt binder according to the gel permeation chromatography (GPC) test results. The Fourier-transform infrared spectroscopy (FTIR) test results did not report detectable changes in functional group of based binder.