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AbstractHelicobacter pylori is a gram-negative bacterium that colonizes the stomach of approximately half of the worldwide population, with higher prevalence in densely populated areas like Asia, the Caribbean, Latin America, and Africa. H. pylori infections range from asymptomatic cases to potentially fatal diseases, including peptic ulcers, chronic gastritis, and stomach adenocarcinoma. The management of these conditions has become more difficult due to the rising prevalence of drug-resistant H. pylori infections, which ultimately lead to gastric cancer and mucosa-associated lymphoid tissue (MALT) lymphoma. In 1994, the International Agency for Research on Cancer (IARC) categorized H. pylori as a Group I carcinogen, contributing to approximately 780,000 cancer cases annually. Antibiotic resistance against drugs used to treat H. pylori infections ranges between 15% and 50% worldwide, with Asian countries having exceptionally high rates. This review systematically examines the impacts of H. pylori infection, the increasing prevalence of antibiotic resistance, and the urgent need for accurate diagnosis and precision treatment. The present status of precision treatment strategies and prospective approaches for eradicating infections caused by antibiotic-resistant H. pylori will also be evaluated. [ABSTRACT FROM AUTHOR]

[Display omitted] • The current review describes bacterial classification using SERS for the identification of pathogens for clinical application diagnosis. • This review provides a brief overview of the mechanism and evolution of the SERS diagnostic principle for pathogenic bacteria. • Discussed the several novel SERS-compatible technologies in clinical applications and computational challenges of pre-processing spectra. • Its highlights the limitations and perspectives of the SERS technique. • It summarizes the potential applications for direct bacterial diagnosis in clinical samples such as blood, urine and sputum. The rapid and reliable detection of pathogenic bacteria at an early stage is a highly significant research field for public health. However, most traditional approaches for pathogen identification are time-consuming and labour-intensive, which may cause physicians making inappropriate treatment decisions based on an incomplete diagnosis of patients with unknown infections, leading to increased morbidity and mortality. Therefore, novel methods are constantly required to face the emerging challenges of bacterial detection and identification. In particular, Raman spectroscopy (RS) is becoming an attractive method for rapid and accurate detection of bacterial pathogens in recent years, among which the newly developed surface-enhanced Raman spectroscopy (SERS) shows the most promising potential. Recent advances in pathogen detection and diagnosis of bacterial infections were discussed with focuses on the development of the SERS approaches and its applications in complex clinical settings. The current review describes bacterial classification using surface enhanced Raman spectroscopy (SERS) for developing a rapid and more accurate method for the identification of bacterial pathogens in clinical diagnosis. The initial part of this review gives a brief overview of the mechanism of SERS technology and development of the SERS approach to detect bacterial pathogens in complex samples. The development of the label-based and label-free SERS strategies and several novel SERS-compatible technologies in clinical applications, as well as the analytical procedures and examples of chemometric methods for SERS, are introduced. The computational challenges of pre-processing spectra and the highlights of the limitations and perspectives of the SERS technique are also discussed. Taken together, this systematic review provides an overall summary of the SERS technique and its application potential for direct bacterial diagnosis in clinical samples such as blood, urine and sputum, etc. [ABSTRACT FROM AUTHOR]

Among the limited studies that have investigated flow experience in mobile advertising, the focus is cast on the value of advertising and the impact of flow experience. This study investigates the factors of mobile advertising that affect purchase intentions based on the value of context awareness and flow experience. First, a literature review of the corresponding studies and confirmatory factor analysis are combined to identify key factors that influence the purchase intentions of cell phones. Second, analytic network process (ANP) and structural equation modeling (SEM) are integrated into an SEM–ANP multi-criteria evaluation model. Results show that the weights for credibility, entertainment, focused immersion, and intrinsic interest are the highest. Furthermore, consumers believe that mobile advertising is a good informational reference for purchase decisions, and that the interaction of advertising value and the value of flow experience affect purchase intentions. Compared to informational advertisements, transformational advertisements are found to have a better effect on stimulating purchase intentions. Marketers are suggested to focus on transformational advertisements, supplemented by informational advertisements when designing mobile advertising campaigns. [ABSTRACT FROM AUTHOR]

There are many commercially available glycogen particles in the market due to their bioactive functions as food additive, drug carrier and natural moisturizer, etc. It would be beneficial to rapidly determine the origins of commercially-available glycogen particles, which could facilitate the establishment of quality control methodology for glycogen-containing products. With its non-destructive, label-free and low-cost features, surface enhanced Raman spectroscopy (SERS) is an attractive technique with high potential to discriminate chemical compounds in a rapid mode. In this study, we applied the combination of SERS technique and machine leaning algorithms on glycogen analysis, which successfully predicted the origins of glycogen particles from a variety of organisms with convolutional neural network (CNN) algorithm plus attention mechanism having the best computational performance (5-fold cross validation accuracy = 96.97 %). In sum, this is the first study focusing on the discrimination of commercial glycogen particles originated from different organisms, which holds the application potential in quality control of glycogen-containing products. [Display omitted] • AgNPs substrate greatly enhances the Raman intensity and information richness for glycogen particles. • PCA and t-SNE are able to cluster SERS spectra of different glycogen samples into different groups. • Supervised machine learning algorithms predict the organismal origins of glycogen with high accuracy and robustness. • Computational analyses consistently achieved better results via SERS spectra than RS spectra. [ABSTRACT FROM AUTHOR]

Under hydrothermal conditions a new Cd(II) polymer [Cd(dic)]n1 (H4dic = 5-(3′,4′-Dicarboxylphenoxy)-isophthalic acid) was synthesized. The compound crystallizes in the space group C2 and the Monoclinic system, with b = 8.0043(9), a = 18.523(2), c = 16.5238(19) Å, β = 118.742(2)°,α = 90°, γ = 90°, Z = 1, V = 2148.1(4) Å3, Mr = 2728.38, Dc = 2.109 Mg/m3, F(000) = 1332, μ = 2.059 mm−1, the final wR = 0.0801 and R = 0.0317 for 3598 with I > 2σ(I) observed reflections. A three-dimensional (3D) network of the compound presents extended by both btc4- anions for a chelating coordination mode in which the dic4- anions employ. From the topology point of view, the structure with (4.62)(4.65.84) topology net could be described as a (3,5)-connected 3D network. Elemental analyses, Infrared spectroscopy, powder X-ray diffraction properties of 1 are also investigated and thermogravimetric analysis. [ABSTRACT FROM AUTHOR]

[Display omitted] • SERS spectral deconvolution revealed unique characteristic peaks for Shigella spp. • Label-free SERS paired with 1DMSCNN achieved best prediction for Shigella spp. • Software was developed to automatically predict Shigella spp. via SERS spectra. Accurate discrimination of Shigella spp. sits in the core of shigellosis prevention and control. As a label-free method, surface enhanced Raman spectroscopy (SERS) is being intensively investigated for bacterial diagnostics. In this study, we developed a novel method for rapid and accurate discrimination of Shigella spp. via label-free SERS coupling with multiscale deep-learning method. In particular, SERS spectral deconvolution was used to generate unique barcodes, revealing subtle differences in molecular composition between Shigella spp. Four supervised learning models based on Random Forest (RF), Support Vector Machine (SVM), Convolutional Neural Network (CNN), and One-Dimensional Multi-Scale CNN (1DMSCNN) were constructed and assessed for their predictive capacities of Shigella spp. The results showed that 1DMSCNN achieved the best performance, which could quickly distinguish four Shigella spp. accurately. Finally, we built a software embedded with 1DMSCNN model to predict raw SERS spectra of Shigella spp., which is freely available at https://github.com/4forfull/1DMSCNN_RAMAN_SHIGELLA. [ABSTRACT FROM AUTHOR]

Extant studies on marketing strategic alliance development lack systematic measurement models; consequently, they cannot provide a holistic picture of the relationship evaluation stage. In addition, it is difficult to clearly understand the interactive effects between the critical elements of marketing strategic alliance development. Therefore, this study proposes a systematic measurement model, called the hierarchy structural fuzzy analytical network process model (H-S FANP model), to evaluate the correlation, interaction, and mutual dependence of the critical elements at the evaluation stage. This model combines four methods, i.e., the interpretation of structural model, Matrice d’ Impacts Croisés Multiplication Appliquée à un Classement, fuzzy linguistic preference relations, and analytical network process (ANP), to overcome various problems encountered when using the conventional ANP. To illustrate how the H-S FANP model can be applied, this study uses the mobile telecommunications industry in Taiwan as an empirical subject. The findings show that the H-S FANP model can assist the mobile telecommunications industry in its long-term marketing strategic alliance development and help decision-makers in improving their evaluation quality and calculation efficiency when analyzing critical elements during the evaluation stage of development. [ABSTRACT FROM AUTHOR]

Network-on-chip (NoC) is an emerging interconnect infrastructure to address the scalability limitation of conventional shared bus architecture for many-core system-on-chip (MCSoC). Current field-programmable gate arrays (FPGAs) have over million lookup tables, making it possible to prototype a complete NoC-based MCSoC on a single FPGA device. FPGA prototyping allows rapid system verification and optimum design parameters estimation. However, existing NoC-based MCSoC prototypes are usually adopting simple NoC architectural functionality. These NoC prototypes cannot represent a realistic projection of the state-of-the-art application-specific integrated circuit (ASIC) NoCs as these prototypes have limited overall system performance. This paper presents ProNoC, an integrated tool for rapid prototyping and validation of NoC-based MCSoC projects targeting FPGA devices. ProNoC adopts most advanced NoC features such as the support of virtual channel (VC), virtual network, low latency routing and different routing algorithms. Results show that NoC interconnect in ProNoC outperforms CONNECT, the most recent VC based prototype NoC with lower logic cell utilization, higher maximum operating frequency, higher average saturation throughput, and lower average communication latency. Moreover, ProNoC is equipped with graphical user interface to facilitate the development of MCSoC prototypes on FPGA platforms. [ABSTRACT FROM AUTHOR]

Bacterial species within the Acinetobacter baumannii-calcoaceticus (Acb) complex are very similar and are difficult to discriminate. Misidentification of these species in human infection may lead to severe consequences in clinical settings. Therefore, it is important to accurately discriminate these pathogens within the Acb complex. Raman spectroscopy is a simple method that has been widely studied for bacterial identification with high similarities. In this study, we combined surfaced-enhanced Raman spectroscopy (SERS) with a set of machine learning algorithms for identifying species within the Acb complex. According to the results, the support vector machine (SVM) model achieved the best prediction accuracy at 98.33% with a fivefold cross-validation rate of 96.73%. Taken together, this study confirms that the SERS-SVM method provides a convenient way to discriminate between A. baumannii, Acinetobacter pittii, and Acinetobacter nosocomialis in the Acb complex, which shows an application potential for species identification of Acinetobacter baumannii-calcoaceticus complex in clinical settings in near future. [ABSTRACT FROM AUTHOR]

Diabetes is a chronic disease that poses a serious threat to health, and its early risk prediction has been a hot research topic in the field of medical artificial intelligence. Routine medical checkups are the most common way to monitor people's health status, and the data from medical checkups contain rich diagnostic information, which is valuable for diabetes risk prediction. Currently, most of the available studies on diabetes risk prediction are based on publicly available datasets, and the models and algorithms do not work well on real clinical datasets. Real routine checkup data are characterized by complex information, diverse features, high redundancy and poor balance, which pose great challenges for diabetes risk prediction. To address this problem, this paper proposes a multi-strategy data augmentation-based diabetes risk prediction method, after completing data pre-processing and feature selection, a counterfactual-based data balancing strategy is used to augment a minority class of instances, and a density clustering-based supplemental counterfactual data augmentation strategy is proposed to address the problem of insufficient representation of generated instances in the counterfactual method. Moreover, the uncertainty-weighted method is used in the model training phase. Based on the real checkup dataset, five machine learning methods including Logistic Regression (LR), SVM, Decision Tree, Random Forest and Gradient Boosting are used to model and use 5-fold cross-validation to carry out diabetes risk assessment and prediction. The experimental results showed that the sensitivity and precision of the models were significantly improved compared with the existing methods, and the sensitivity of the LR model for diabetes risk prediction on the real routine checkup dataset reached more than 90 % , which meet the requirements of clinical application. [ABSTRACT FROM AUTHOR]

Purpose: As a simple and invasive treatment, arthroscopic medial meniscal posterior horn resections (MMPHRs) can relieve the obstructive symptoms of medial meniscus posterior root tears (MMPRTs) but with the risk of aggravating biomechanical changes of the joint. The aim of this study was to analyze dynamic simulation of the knee joint after medial meniscus posterior root tear and posterior horn resection. Methods: This study established static and dynamic models of MMPRTs and MMPHRs on the basis of the intact medial meniscus model (IMM). In the finite element analysis, the three models were subjected to 1000 N axial static load and the human walking gait load defined by the ISO14243-1 standard to evaluate the influence of MMPRTs and MMPHRs on knee joint mechanics during static standing and dynamic walking. Results: In the static state, the load ratio of the medial and lateral compartments remained nearly constant (2:1), while in the dynamic state, the load ratio varied with the gait cycle. After MMPHRs, at 30% of the gait cycle, compared with the MMPRTs condition, the maximum von Mises stress of the lateral meniscus (LM) and the lateral tibial cartilage (LTC) were increased by 166.0% and 50.0%, respectively, while they changed by less than 5% during static analysis. The maximum von Mises stress of the medial meniscus (MM) decreased by 55.7%, and that of the medial femoral cartilage (MFC) increased by 53.5%. Conclusion: After MMPHRs, compared with MMPRTs, there was no significant stress increase in articular cartilage in static analysis, but there was a stress increase and concentration in both medial and lateral compartments in dynamic analysis, which may aggravate joint degeneration. Therefore, in clinical treatments, restoring the natural structure of MMPRTs is first recommended, especially for physically active patients. [ABSTRACT FROM AUTHOR]

Hypoxia upregulates hypothalamic corticotrophin releasing hormone (CRH) and its receptor type-1 (CRHR1) expression and activates the HPA axis and induces hypoxic sickness and behavioral change. The transcriptional mechanism by which hypoxia differently regulates CRHR1 expression remains unclear. Here we report hypoxia time-dependently induced biphasic expression of CRHR1mRNA in rat pituitary during different physiological status. Short exposure of gestational dams to hypoxia reduced CRHR1mRNA in the pituitary of P1-P14 male rat offspring. A short- and prolonged-hypoxia evoked biphasic response of CRHR1mRNA characterized initially by decreases and subsequently by persistent increases, mediated by a rapid negative feedback via CRHR1 signaling and positive transcriptional control via NF-κB, respectively. Further analysis of CRHR1 promoter in cultured primary anterior pituitary and AtT20 cells showed that c-Jun/AP-1 delivered negative while HIF-1α and NF-κB delivered positive control of transcription at CRHR1 promoter. The negative and positive inputs are integrated by hypoxic initiation and duration in CRHR1 transcription. [ABSTRACT FROM AUTHOR]

Molecular mechanisms behind structural alterations between fragile and stable glycogen α particles in liver are not clear yet. In this pilot study, we re-examined the diurnal alterations of glycogen structure from the perspective of liver tissue transcriptome. By comparing the structures of liver glycogen from mice at 12 am, 8 am, 12 pm, and 8 pm (light-on: 6 am; light-off: 6 pm), we re-confirmed that the liver glycogen was fragile at 12 am and 8 am and stable at 12 pm and 8 pm as previously reported. The structural differences of glycogen particles at 12 am and 12 pm were thoroughly compared via transcriptomics. Differentially expressed genes (DEGs) with statistical significance were identified, while expression level of the gene ppp1r3g (log 2 Fold_Change = −6.368, P -value = 2.89E−04) that encoded PPP1R3G with glycogen binding domain was most significantly changed, which provided preliminary clues to the structural alterations of glycogen α particles during the diurnal cycle. [Display omitted] [ABSTRACT FROM AUTHOR]

Introduction Acute tubulointerstitial nephritis (ATIN) is a common cause of acute kidney injury with various etiologies. It has been shown that autoimmune-related ATIN (AI-ATIN) has a higher recurrence rate and a greater likelihood of developing into chronic kidney disease compared with drug-induced ATIN, yet misdiagnosis at renal biopsy is not uncommon. Methods Patients who were clinicopathologically diagnosed as ATIN from January 2006 to December 2015 in Peking University First Hospital were enrolled. Clinical, pathological and follow-up data were collected. Serum samples on the day of renal biopsy were collected and tested for anti-C-reactive protein (CRP) antibodies. CRP and its linear peptides were used as coating antigens to detect antibodies. Statistical analysis was used to assess the diagnostic value of the antibodies. Results Altogether 146 patients were enrolled. The receiver operating characteristic–area under the curve of the anti-CRP antibody for the identification of late-onset AI-ATIN was 0.750 (95% confidence interval 0.641–0.860, P < 0.001) and the positivity was associated with ATIN relapse (adjusted hazard ratio = 4.321, 95% confidence interval 2.402–7.775, P < 0.001). Antibodies detected by CRP linear peptide 6 (PT6) were superior with regard to differentiating patients with AI-ATIN, while antibodies detected by peptide 17 (PT17) could predict ATIN relapse. Antibodies detected by these two peptides were positively correlated with the severity of tubular dysfunction and pathological injury. Conclusions Serum anti-CRP antibody could be used to differentiate late-onset AI-ATIN and predict relapse of ATIN at the time of renal biopsy. The CRP linear peptides PT6 and PT17 could be used as coating antigens to detect anti-CRP antibodies, which may provide more information for the clinical assessment of ATIN. [ABSTRACT FROM AUTHOR]

Nowadays, service-oriented marketing has been playing an important role in marketing science fields. The current studies have focused on the establishment of a brand equity model and the relevant causal relationships of the model, they have not presented any consistent measurement technique. Hence, this paper aims to standardize the estimation of a constructed dimension for the equity of service-oriented brands and to solve the multiple-dimension problem inherent in this estimation. In particular, this proposed analytical model considers distinct weights for brand equity categories and attributes. Further, we intend to systematically present a deliberate procedure of the brand equity model along with a strategy to enable the further development of this procedure. By adopting quality function deployment (QFD) and consistent fuzzy preference relations, we create a valid and reliable brand equity model for hospitality firms. Finally, we empirically assess the measurement and managerial strategies related to the proposed model by illustrating the case of a restaurant chain. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to evaluate multiple criteria and sub-criteria of e-SQ with the interdependence perspective, utilising three phases of measurement for the proposed e-SQ evaluation. Design/methodology/approach – The paper utilises literature reviews to address the question of interdependence in the context of e-SQ and constructs an interdependent network structure for e-SQ evaluation. Then a method and three phases of measurement are proposed that combine the consistent fuzzy preference relations method with the analytic network process (ANP) technique, to evaluate e-SQ by using senior experts who work at travel web site companies as research participants. Findings – First, this study discovered the interdependence perspective of criteria and sub-criteria for e-SQ evaluation. Second, it was found out that the weights of criteria and sub-criteria have reverse situations after considering the interdependence perspective. Third, the findings indicate that the interdependence perspective among criteria and sub-criteria should be taken into consideration, and the authors remind practitioners of the need to implement overall improvements instead of independently addressing each criterion or sub-criterion of e-SQ individually. Originality/value – The authors propose a scientific and systematic method for e-SQ evaluation that can enable managers of online web sites to determine the important factors, and further to achieve total e-SQ control management. Moreover the proposed method can deal with imprecise information when evaluating e-SQ, as well as considering interdependent relationships among factors, and is thus faster and more efficient at addressing the inconsistency problems involved in multiple decision making than conventional methods. [ABSTRACT FROM AUTHOR]

Abstract: Mesoporous films and monoliths with different thicknesses have been synthesized through evaporation-induced self-assembly in the presence of nonionic block copolymer templates. At the same reactant molar ratio, mesoporous thin films (∼300–500nm in thickness) dip-coated on glass substrates have two-dimensional(2D) hexagonal mesostructures (p6m), while monoliths (∼1mm in thickness) formed in containers have centered rectangular structures (cmm). The different evaporation time in the two cases leads to different condensation extent of the silica species and finally induces different mesostructures. Water also plays an important role in the evaporation process and the range of water ratio in starting components where monoliths with centered rectangular structures are favored has been studied. As-synthesized monoliths with cmm structure show a certain degree of thermal stability during calcination, but are not stable during hydrothermal treatment and undergo a structure evolution to p6m; however, the calcined monoliths with cmm structure are hydrothermally stable, possibly due to its thick silica walls. [Copyright &y& Elsevier]

Five new phenanthrene derivatives: 9-ethoxy-7-methoxy-aristololactam IV (1) , norcepharadione A N - β - d -glucopyranoside (2) , aristololactamoside I (3) , aristololactamoside II (4) and aristothiolactoside (5) together with eleven known phenanthrene derivatives ( 6 – 16 ) were isolated from the ethanol extract of the roots and rhizomes of Asarum heterotropoides var. mandshuricum . The aristololactams with substitution of ethoxy at C-9 position ( 1 , 9 , and 10 ) and the sulfur-containing phenanthrene derivative ( 5 ) were reported in the genus Asarum for the first time. Furthermore, six phenanthrene glucoside derivatives ( 2 – 5 , 13 and 14 ) were also found in this genus for the first time and compounds 7 and 9 – 15 were isolated from the genus Asarum for the first time. Six of them ( 1 , 2 , 9 , 10 , 13 and 14 ) were submitted to cytotoxicity test against human renal proximal tubular epithelial cell lines (HK-2) using MTT and LDH assays. Compounds 1 and 10 showed significant cytotoxic activity against HK-2 cell lines with IC 50 values of 18.18 and 20.44 μmol/L in MTT assay and 84.36 and 35.06 μmol/L in LDH assay, respectively. Compound 9 showed moderate cytotoxicity in MTT assay with IC 50 values of 95.60 μmol/L, but no cytotoxicity in LDH assay. Compounds 2 , 13 and 14 showed cytotoxic effect in neither MTT assay nor LDH assay. Considering the other nephrotoxic phenanthrene derivatives ( 6 , 8 , 12 , 15 and 16 ) previously tested, the results implied the potency of renal toxicity of this herb used as a medicine. [ABSTRACT FROM AUTHOR]

It has been reported that glycogen in Escherichia coli has two structural states, that is, fragility and stability, which alters dynamically. However, molecular mechanisms behind the structural alterations are not fully understood. In this study, we focused on the potential roles of two important glycogen degradation enzymes, glycogen phosphorylase (glgP) and glycogen debranching enzyme (glgX), in glycogen structural alterations. The fine molecular structure of glycogen particles in Escherichia coli and three mutants (Δ glgP , Δ glgX and Δ glgP /Δ glgX) were examined, which showed that glycogen in E. coli Δ glgP and E. coli Δ glgP /Δ glgX were consistently fragile while being consistently stable in E. coli Δ glgX , indicating the dominant role of GP in glycogen structural stability control. In sum, our study concludes that glycogen phosphorylase is essential in glycogen structural stability, leading to molecular insights into structural assembly of glycogen particles in E. coli. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: High-altitude cerebral edema (HACE) is the severe type of acute mountain sickness (AMS) and life threatening. A subclinical inflammation has been speculated, but the exact mechanisms underlying the HACE are not fully understood. Methods: Human volunteers ascended to high altitude (3860 m, 2 days), and rats were exposed to hypoxia in a hypobaric chamber (5000 m, 2 days). Human acute mountain sickness was evaluated by the Lake Louise Score (LLS), and plasma corticotrophin-releasing hormone (CRH) and cytokines TNF-α, IL-1β, and IL-6 were measured in rats and humans. Subsequently, rats were pre-treated with lipopolysaccharide (LPS, intraperitoneal (ip) 4 mg/kg, 11 h) to induce inflammation prior to 1 h hypoxia (7000 m elevation). TNF-α, IL-1β, IL-6, nitric oxide (NO), CRH, and aquaporin-4 (AQP4) and their gene expression, Evans blue, Na(+)-K(+)-ATPase activity, p65 translocation, and cell swelling were measured in brain by ELISA, Western blotting, Q-PCR, RT-PCR, immunohistochemistry, and transmission electron micrography. MAPKs, NF-κB pathway, and water permeability of primary astrocytes were demonstrated. All measurements were performed with or without LPS challenge. The release of NO, TNF-α, and IL-6 in cultured primary microglia by CRH stimulation with or without PDTC (NF-κB inhibitor) or CP154,526 (CRHR1 antagonist) were measured. Results: Hypobaric hypoxia enhanced plasma TNF-α, IL-1β, and IL-6 and CRH levels in human and rats, which positively correlated with AMS. A single LPS injection (ip, 4 mg/kg, 12 h) into rats increased TNF-α and IL-1β levels in the serum and cortex, and AQP4 and AQP4 mRNA expression in cortex and astrocytes, and astrocyte water permeability but did not cause brain edema. However, LPS treatment 11 h prior to 1 h hypoxia (elevation, 7000 m) challenge caused cerebral edema, which was associated with activation of NF-κB and MAPKs, hypoxia-reduced Na(+)-K(+)-ATPase activity and blood-brain barrier (BBB) disruption. Both LPS and CRH stimulated TNF-α, IL-6, and NO release in cultured rat microglia via NF-κB and cAMP/PKA. Conclusions: Preexisting systemic inflammation plus a short severe hypoxia elicits cerebral edema through upregulated AQP4 and water permeability by TLR4 and CRH/CRHR1 signaling. This study revealed that both infection and hypoxia can cause inflammatory response in the brain. Systemic inflammation can facilitate onset of hypoxic cerebral edema through interaction of astrocyte and microglia by activation of TLR4 and CRH/CRHR1 signaling. Anti-inflammatory agents and CRHR1 antagonist may be useful for prevention and treatment of AMS and HACE. [ABSTRACT FROM AUTHOR]

[Display omitted] Podocyte injury following abnormal podocyte autophagy plays an indispensable role in diabetic nephropathy (DN), therefore, restoration of podocyte autophagy is considered as a feasible strategy for the treatment of DN. Here, we investigated the preventive effects of sarsasapogenin (Sar), the main active ingredient in Anemarrhena asphodeloides Bunge , on the podocyte injury in diabetic rats, and tried to illustrate the mechanisms underlying the effects in high glucose (HG, 40 mM)-treated podocytes (MPs). Diabetes model was established in rats with single streptozocin (60 mg· kg−1) intraperitoneal administration. The rats were then treated with Sar (20, 60 mg· kg−1· d−1, i.g.) or a positive control drug insulin (INS) (40 U· kg−1· d−1, i.h.) for 10 weeks. Our results showed that both Sar and insulin precluded the decreases of autophagy-related proteins (ATG5, Beclin1 and LC3B) and podocyte marker proteins (podocin, nephrin and synaptopodin) in the diabetic kidney. Furthermore, network pharmacology was utilized to assess GSK3β as the potential target involved in the action of Sar on DN and were substantiated by significant changes of GSK3β signaling in the diabetic kidney. The underlying protection mechanisms of Sar were explored in HG-treated MPs. Sar (20, 40 μM) or insulin (50 mU/L) significantly increased the expression of autophagy- related proteins and podocyte marker proteins in HG-treated MPs. Furthermore, Sar or insulin treatment efficiently regulated phosphorylation at activation and inhibition sites of GSK3β. To sum up, this study certifies that Sar meliorates experimental DN through targeting GSK3β signaling pathway and restoring podocyte autophagy. [ABSTRACT FROM AUTHOR]