Prediction model for delayed behavior of early ambulation after surgery for varicose veins of lower extremity: a prospective case‒control study.

OBJECTIVE: To analyse influencing factor and establish a prediction model for delayed behavior of early ambulation after surgery for varicose veins of lower extremity (VVLE). DESIGN: A prospective case‒control study. SETTING: VVLE patients were recruited from two local hospitals. PARTICIPANTS: 498 patients with VVLE were selected by convenience sampling and divided into a training set and test set. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Participants were collected information before surgery and followed up until the day after surgery, then divided into a normal and delayed ambulation group. Propensity score matching (PSM) was applied in all participants by type of surgery and anaesthesia. All information of two groups were compared using logistic regression, back propagation neural network (BPNN) and decision tree models. The accuracy, sensitivity, specificity, and area under the curve (AUC) of three models were compared to determine the optimal model. RESULTS: A total of 406 participants were included after PSM. The AUCs of training sets of logistic regression, BPNN and decision tree models were 0.850, 0.932, and 0.757, respectively. The AUCs of test sets were 0.928, 0.984, and 0.776, respectively. BPNN was the optimal model. SSRS score, preoperative 30-second sit-stand test score, CEAP grade, MCMQ score and whether you know the need for early ambulation, in descending order of the result of BPNN model. A probability value greater than 0.56 indicated delayed early ambulation. CONCLUSIONS: Clinicians should pay more attention to those with lower SSRS score, poor lower limb strength, higher CEAP grade and poor medical coping ability, and make patients aware of the necessity and importance of early ambulation, thereby assisting decision-making regarding postoperative rehabilitation. Further research is needed to improve the method, add more variables and transform the model into a scale to screen and intervene in the delay behavior of early ambulation of VVLE in advance.

A multiplier-free Rulkov neuron under memristive electromagnetic induction: Dynamics analysis, energy calculation, and circuit implementation.

Establishing a realistic and multiplier-free implemented biological neuron model is significant for recognizing and understanding natural firing behaviors, as well as advancing the integration of neuromorphic circuits. Importantly, memristors play a crucial role in constructing memristive neuron and network models by simulating synapses or electromagnetic induction. However, existing models lack the consideration of initial-boosted extreme multistability and its associated energy analysis. To this end, we propose a multiplier-free implementation of the Rulkov neuron model and utilize a periodic memristor to represent the electromagnetic induction effect, thereby achieving the biomimetic modeling of the non-autonomous memristive Rulkov (mRulkov) neuron. First, theoretical analysis demonstrates that the stability distribution of the time-varying line equilibrium point is determined by both the parameters and the memristor's initial condition. Furthermore, numerical simulations show that the mRulkov neuron can exhibit parameter-dependent local spiking, local hidden spiking, and periodic bursting firing behaviors. In addition, based on the periodic characteristics of the memductance function, the topological invariance of the mRulkov neuron is comprehensively proved. Therefore, local basins of attraction, bifurcation diagrams, and attractors related to extreme multistability can be boosted by switching the memristor's initial condition. Significantly, the novel boosted extreme multistability is discovered in the Rulkov neuron for the first time. More importantly, the energy transition associated with the boosting dynamics is revealed through computing the Hamilton energy distribution. Finally, we develop a simulation circuit for the non-autonomous mRulkov neuron and confirm the effectiveness of the multiplier-free implementation and the accuracy of the numerical results through PSpice simulations.

Identification of the metabolites of n-butylidenephthalide in rat and human liver microsomes by liquid chromatography-high-resolution mass spectrometry.

n-Butylidenephthalide (NBDP) is one of the bioactive constituents originally isolated from Ligusticum chuanxiong Hort. The aim of this study was to study the metabolic profiles of NBDP in rat and human liver microsomes. NBDP was individually incubated with liver microsomes of rat and human at 37°C for 1 h and the samples incubated were analyzed by ultra-high-performance liquid chromatography combined with high-resolution mass spectrometry. The identities of the metabolites were identified by accurate masses, product ions and retention times. Under the current conditions, a total of 14 metabolites were detected and identified. M12, M13 and M14 were biosynthesized and unambiguously characterized by nuclear magnetic resonance spectroscopy. All the metabolites can be detected in rat liver microsomes, whereas in human liver microsomes, M1, M3, M4, M5, M6 and M7 were not detected. Our results demonstrated that the metabolic pathways of NBDP included hydroxylation, hydration, hydrolysis and glutathione conjugation. This study provides an overview of the metabolic profiles of NBDP in vitro, which is helpful to understand the action of this compound.

Baicalin Inhibits Renal Cell Apoptosis and Protects Against Acute Kidney Injury in Pediatric Sepsis.

BACKGROUND Pediatric sepsis has high morbidity in children, may lead to acute kidney injury (AKI), and further aggravate the disease. Baicalin is a kind of flavonoid in Scutellaria baicalensis Georgi and has been reported to protect against several diseases, but its roles in septic AKI remain unclear. This study aimed to uncover the effects of baicalin in AKI during pediatric sepsis. MATERIAL AND METHODS Blood urea nitrogen (BUN) and serum creatinine (Cr) levels were detected in 50 pediatric patients, who underwent basic therapy with or without baicalin adjunctive therapy. Mouse sepsis models were constructed by cecal ligation and puncture (CLP) and treated with baicalin intragastrically, after which BUN and Cr examination, TUNEL apoptosis assay, and expression analyses of BAX and BCL2 were performed. RESULTS Baicalin adjunctive therapy significantly decreased BUN and Cr levels in pediatric sepsis patients (P<0.05). CLP led to elevated BUN and Cr levels in the mouse model (P<0.01), indicating kidney injury accompanied by sepsis. Baicalin decreased BUN and Cr levels (P<0.05), and reduced the apoptotic cell percent in the renal tissue (P<0.05) of the CLP model. It inhibited BAX and promoted BCL2 in the renal tissue, which was consistent with cell apoptosis changes. CONCLUSIONS Baicalin is capable of suppressing renal cell apoptosis and protecting against AKI in pediatric sepsis. This study provides a potential adjunctive therapy for treating AKI in pediatric sepsis, and further research is necessary to reveal its deeper mechanisms.

Spatiotemporal variations of reference crop evapotranspiration in Northern Xinjiang, China.

To set up a reasonable crop irrigation system in the context of global climate change in Northern Xinjiang, China, reference crop evapotranspiration (ET0) was analyzed by means of spatiotemporal variations. The ET0 values from 1962 to 2010 were calculated by Penman-Monteith formula, based on meteorological data of 22 meteorological observation stations in the study area. The spatiotemporal variations of ET0 were analyzed by Mann-Kendall test, Morlet wavelet analysis, and ArcGIS spatial analysis. The results showed that regional average ET0 had a decreasing trend and there was an abrupt change around 1983. The trend of regional average ET0 had a primary period about 28 years, in which there were five alternating stages (high-low-high-low-high). From the standpoint of spatial scale, ET0 gradually increased from the northeast and southwest toward the middle; the southeast and west had slightly greater variation, with significant regional differences. From April to October, the ET0 distribution significantly influenced the distribution characteristic of annual ET0. Among them sunshine hours and wind speed were two of principal climate factors affecting ET0.

Memristor-induced hyperchaos, multiscroll and extreme multistability in fractional-order HNN: Image encryption and FPGA implementation.

Fractional-order differentiation (FOD) can record information from the past, present, and future. Compared with integer-order systems, FOD systems have higher complexity and more accurate ability to describe the real world. In this paper, two types of fractional-order memristors are proposed and one type is proved to have extreme multistability, local activity, and non-volatility. By using memristors to simulate the autapse of a neuron and to describe the phenomenon of electromagnetic induction caused by electromagnetic radiation, we establish a new 5D FOD memristive HNN (FOMHNN). Through dynamic simulation, rich dynamic behaviors are found, such as hyperchaos, multiscroll, extreme multistability, and "overclocking" behavior caused by order reduction. To the best of our knowledge, this is the first time that such rich dynamic behaviors are found in FOMHNN simultaneously. Based on this FOMHNN, a very efficient and secure image encryption scheme is designed. Security analysis shows that the encrypted Lena image has extremely low adjacent pixel correlation and high randomness, with information entropy of 7.9995. Despite discarding diffusion and scrambling, it has excellent plaintext sensitivity, with NCPR = 99.6095% and UACI = 33.4671%. Finally, this paper implements the proposed FOMHNN and image encryption on field programmable gate array (FPGA). To our knowledge, the related work of fully hardware implementation of fractional-order neural networks and image encryption schemes based on this is rare.

Risk stratification and survival time of patients with gram-negative bacillary pneumonia in the intensive care unit.

Introduction: Pneumonia is a common infection in the intensive care unit (ICU), and gram-negative bacilli are the most common bacterial cause. The purpose of the study was to investigate the risk factors for 30-day mortality in patients with gram-negative bacillary pneumonia in the ICU, construct a predictive model, and stratify patients based on risk to assess their short-term survival. Methods: Patients admitted to the ICU with gram-negative bacillary pneumonia at Fujian Medical University Affiliated First Hospital between January 2018 and September 2020 were selected. Patients were divided into deceased and survivor groups based on whether death occurred within 30 days. Multifactorial logistic regression analysis was used to identify independent risk factors for 30-day mortality in these patients, and a predictive nomogram model was constructed based on these factors. Patients were categorized into low-, medium-, and high-risk groups according to the model's predicted probability, and Kaplan-Meier survival curves were plotted to assess short-term survival. Results: The study included 305 patients. Lactic acid (odds ratio [OR], 1.524, 95% CI: 1.057-2.197), tracheal intubation (OR: 4.202, 95% CI: 1.092-16.169), and acute kidney injury (OR:4.776, 95% CI: 1.632-13.978) were identified as independent risk factors for 30-day mortality. A nomogram prediction model was established based on these three factors. Internal validation of the model showed a Hosmer-Lemeshow test result of X2=5.770, P=0.834, and an area under the ROC curve of 0.791 (95% CI: 0.688-0.893). Bootstrap resampling of the original data 1000 times yielded a C-index of 0.791, and a decision curve analysis indicated a high net benefit when the threshold probability was between 15%-90%. The survival time for low-, medium-, and high-risk patients was 30 (30, 30), 30 (16.5, 30), and 17 (11, 27) days, respectively, which were significantly different. Conclusion: Lactic acid, tracheal intubation, and acute kidney injury were independent risk factors for 30-day mortality in patients in the ICU with gram-negative bacillary pneumonia. The predictive model constructed based on these factors showed good predictive performance and helped assess short-term survival, facilitating early intervention and treatment.

Elevated LDL-c may warn of the risk of gallbladder stones in the patients with metabolic dysfunction-associated steatotic liver disease: A case-control study.

PURPOSE: This study aimed to explore the relationship between metabolic dysfunction-associated steatotic liver disease (MASLD) and the development of new-onset gallbladder stone disease (GSD) and to identify factors that influence the occurrence of new-onset GSD in patients with MASLD. METHODS: In this retrospective case-control study, patients who underwent asymptomatic GSD screening during annual routine health check-ups at two hospitals in China between August 2017 and July 2022 were included. Patients with new-onset GSD and controls without GSD were matched 1:1 based on age, sex, race, occupation, diet, drinking habits, systolic blood pressure, diastolic blood pressure, and fasting blood glucose levels. RESULTS: The study comprised 1200 patients with new-onset GSD and 1200 controls without GSD. Patients with new-onset GSD had higher rates of MASLD (33.8% vs. 22.2 %, P < 0.001) and hypercholesterolemia (12.6% vs. 7.2 %, P < 0.001) compared to controls. Waist circumference (WC) (OR = 1.042, 95 % CI: 1.022-1.063, P < 0.001), high-density lipoprotein cholesterol (HDL-c) (OR = 0.048, 95 % CI: 0.037-0.062, P < 0.001), triglycerides (OR = 0.819, 95 % CI: 0.699-0.958, P = 0.013), and hypercholesterolemia (OR = 5.023, 95 % CI: 2.735-9.225, P < 0.001) were independently associated with new-onset GSD. Among patients with MASLD, WC (OR = 1.075, 95 % CI: 1.026-1.127, P = 0.003), total cholesterol (TC) (OR = 2.094, 95 % CI: 1.259-3.484, P = 0.004), HDL-c (OR = 0.088, 95 % CI: 0.054-0.142, P < 0.001), and low-density lipoprotein cholesterol (LDL-c) (OR = 4.056, 95 % CI: 2.669-6.163, P < 0.001) were independently associated with new-onset GSD. CONCLUSIONS: The findings indicate that hypercholesterolemia is independently associated with GSD. Among patients with MASLD, hypercholesterolemia also showed an independent association with GSD. Notably, this study is the first to identify serum LDL-c levels as potentially the most significant risk factor for GSD, highlighting that elevated LDL-c could serve as an important indicator for individuals with MASLD.

Development of a nomogram for predicting in-hospital mortality in patients with liver cirrhosis and sepsis.

In this study, we aimed to investigate the risk factors associated with in-hospital mortality in patients with cirrhosis and sepsis, establish and validate the nomogram. This retrospective study included patients diagnosed with liver cirrhosis and sepsis in the Medical Information Mart for Intensive Care IV (MIMIC-IV). Models were compared by the area under the curve (AUC), integrated discriminant improvement (IDI), net reclassification index (NRI) and decision curve analysis (DCA). A total of 1,696 patients with cirrhosis and sepsis were included in the final cohort. Our final model included the following 9 variables: age, heartrate, total bilirubin (TBIL), glucose, sodium, anion gap (AG), fungal infections, mechanical ventilation, and vasopressin. The nomogram were constructed based on these variables. The AUC values of the nomograms were 0.805 (95% CI 0.776-0.833), which provided significantly higher discrimination compared to that of SOFA score [0.684 (95% CI 0.647-0.720)], MELD-Na [0.672 (95% CI 0.636-0.709)] and ABIC [0.674(95% CI 0.638-0.710)]. We established the first nomogram for predicting in-hospital mortality in patients with liver cirrhosis and sepsis based on these factors. This nomogram can performs well and facilitates clinicians to identify people at high risk of in-hospital mortality.

Prepared Radix Polygoni Multiflori and emodin alleviate lipid droplet accumulation in nonalcoholic fatty liver disease through MAPK signaling pathway inhibition.

As one of the most common liver diseases, nonalcoholic fatty liver disease (NAFLD) affects almost one-quarter of the world's population. Although the prevalence of NAFLD is continuously rising, effective medical treatments are still inadequate. Radix Polygoni Multiflori (RPM) is a traditional Chinese herbal medicine. As a processed product of RPM, prepared Radix Polygoni Multiflori (PRPM) has been reported to have antioxidant and anti-inflammatory effects. This study investigated whether PRPM treatment could significantly improve NAFLD. We used recent literature, the Herb database and the SwissADME database to isolate the active compounds of PRPM. The OMIM, DisGeNET and GeneCards databases were used to isolate NAFLD-related target genes, and GO functional enrichment and KEGG pathway enrichment analyses were conducted. Moreover, PRPM treatment in NAFLD model mice was evaluated. The results indicate that the target genes are mainly enriched in the AMPK and de novo lipogenesis signaling pathways and that PRPM treatment improves NAFLD disease in model mice. Here, we found the potential benefits of PRPM against NAFLD and demonstrated in vivo and in vitro that PRPM and its ingredient emodin downregulate phosphorylated P38/P38, phosphorylated ERK1/2 and genes related to de novo adipogenesis signaling pathways and reduce lipid droplet accumulation. In conclusion, our findings revealed a novel therapeutic role for PRPM in the treatment of NAFLD and metabolic inflammation.

Memristive competitive hopfield neural network for image segmentation application.

Image segmentation implementation provides simplified and effective feature information of image. Neural network algorithms have made significant progress in the application of image segmentation task. However, few studies focus on the implementation of hardware circuits with high-efficiency analog calculations and parallel operations for image segmentation problem. In this paper, a memristor-based competitive Hopfield neural network circuit is proposed to deal with the image segmentation problem. In this circuit, the memristive cross array is applied to store synaptic weights and perform matrix operations. The competition module based on the Winner-take-all mechanism is composed of the competition neurons and the competition control circuit, which simplifies the energy function of the Hopfield neural network and realizes the output function. Operational amplifiers and ABM modules are used to integrate operations and process external input information, respectively. Based on these designs, the circuit can automatically implement iteration and update of data. A series of PSPICE simulations are designed to verify the image segmentation capability of this circuit. Comparative experimental results and analysis show that this circuit has effective improvements both in processing speed and segmentation accuracy compared with other methods. Moreover, the proposed circuit shows good robustness to noise and memristive variation.

Event-triggered control for robust exponential synchronization of inertial memristive neural networks under parameter disturbance.

Synchronization of memristive neural networks (MNNs) by using network control scheme has been widely and deeply studied. However, these researches are usually restricted to traditional continuous-time control methods for synchronization of the first-order MNNs. In this paper, we study the robust exponential synchronization of inertial memristive neural networks (IMNNs) with time-varying delays and parameter disturbance via event-triggered control (ETC) scheme. First, the delayed IMNNs with parameter disturbance are changed into first-order MNNs with parameter disturbance by constructing proper variable substitutions. Next, a kind of state feedback controller is designed to the response IMNN with parameter disturbance. Based on feedback controller, some ETC methods are provided to largely decrease the update times of controller. Then, some sufficient conditions are provided to realize robust exponential synchronization of delayed IMNNs with parameter disturbance via ETC scheme. Moreover, the Zeno behavior will not happen in all ETC conditions shown in this paper. Finally, numerical simulations are given to verify the advantages of the obtained results such as anti-interference performance and good reliability.

Carbapenem-resistant gram-negative bacterial infection in intensive care unit patients: Antibiotic resistance analysis and predictive model development.

In this study, we analyzed the antibiotic resistance of carbapenem-resistant gram-negative bacteria (CR-GNB) in intensive care unit (ICU) patients and developed a predictive model. We retrospectively collected the data of patients with GNB infection admitted to the ICU of the First Affiliated Hospital of Fujian Medical University, who were then divided into a CR and a carbapenem-susceptible (CS) group for CR-GNB infection analysis. Patients admitted between December 1, 2017, and July 31, 2019, were assigned to the experimental cohort (n = 205), and their data were subjected to multivariate logistic regression analysis to identify independent risk factors for constructing the nomogram-based predictive model. Patients admitted between August 1, 2019, and September 1, 2020, were assigned to the validation cohort for validating the predictive model (n = 104). The Hosmer-Lemeshow test and receiver operating characteristic (ROC) curve analysis were used to validate the model's performance. Overall, 309 patients with GNB infection were recruited. Of them, 97 and 212 were infected with CS-GNB and CR-GNB, respectively. Carbapenem-resistant Klebsiella pneumoniae (CRKP), carbapenem-resistant Acinetobacter baumannii (CRAB) and carbapenem-resistant Pseudomonas aeruginosa (CRPA) were the most prevalent CR-GNB. The multivariate logistic regression analysis results of the experimental cohort revealed that a history of combination antibiotic treatments (OR: 3.197, 95% CI: 1.561-6.549), hospital-acquired infection (OR: 3.563, 95% CI: 1.062-11.959) and mechanical ventilation ≥ 7 days (OR: 5.096, 95% CI: 1.865-13.923) were independent risk factors for CR-GNB infection, which were then used for nomogram construction. The model demonstrated a good fit of observed data (p = 0.999), with an area under the ROC curve (AUC) of 0.753 (95% CI: 0.685-0.820) and 0.718 (95% CI: 0.619-0.816) for the experimental and validation cohort, respectively. The decision curve analysis results suggested that the model has a high practical value for clinical practice. The Hosmer-Lemeshow test indicated a good fit of the model in the validation cohort (p-value, 0.278). Overall, our proposed predictive model exhibited a good predictive value in identifying patients at high risk of developing CR-GNB infection in the ICU and could be used to guide preventive and treatment measures.

Dissection of Hyperspectral Reflectance to Estimate Photosynthetic Characteristics in Upland Cotton (Gossypium hirsutum L.) under Different Nitrogen Fertilizer Application Based on Machine Learning Algorithms.

Hyperspectral technology has enabled rapid and efficient nitrogen monitoring in crops. However, most approaches involve direct monitoring of nitrogen content or physiological and biochemical indicators directly related to nitrogen, which cannot reflect the overall plant nutritional status. Two important photosynthetic traits, the fraction of absorbed photosynthetically active radiation (FAPAR) and the net photosynthetic rate (Pn), were previously shown to respond positively to nitrogen changes. Here, Pn and FAPAR were used for correlation analysis with hyperspectral data to establish a relationship between nitrogen status and hyperspectral characteristics through photosynthetic traits. Using principal component and band autocorrelation analyses of the original spectral reflectance, two band positions (350-450 and 600-750 nm) sensitive to nitrogen changes were obtained. The performances of four machine learning algorithm models based on six forms of hyperspectral transformations showed that the light gradient boosting machine (LightGBM) model based on the hyperspectral first derivative could better invert the Pn of function-leaves in cotton, and the random forest (RF) model based on hyperspectral first derivative could better invert the FAPAR of the cotton canopy. These results provide advanced metrics for non-destructive tracking of cotton nitrogen status, which can be used to diagnose nitrogen nutrition and cotton growth status in large farms.

Genome-Wide Identification and Analysis of the WNK Kinase Gene Family in Upland Cotton.

With-No-Lysine (WNK) kinases are a subfamily of serine/threonine protein kinases. WNKs are involved in plant abiotic stress response and circadian rhythms. However, members of the WNK subfamily and their responses to abiotic and biotic stresses in Gossypium hirsutum have not been reported. In this study, 26 GhWNKs were identified in G. hirsutum. The gene structure, conserved motifs, and upstream open reading frames (uORFs) of GhWNKs were identified. Moreover, GhWNKs regulation is predicted to be regulated by cis-acting elements, such as ABA responsive element (ABRE), MBS, and MYC. Furthermore, transcription factors including MIKC_MADS, C2H2, TALE, bZIP, Dof, MYB, bHLH, and HD-ZIP are projected to play a regulatory role in GhWNKs. The expression patterns of GhWNKs under normal conditions and biotic and abiotic stresses were evaluated, and their expression was found to vary. The expression patterns of several GhWNKs were induced by infiltration with Verticillium dahliae, suggesting that several GhWNKs may play important roles in the response of cotton to V. dahliae. Interestingly, a homoeologous expression bias within the GhWNKs was uncovered in upland cotton. Homoeologous expression bias within GhWNKs provides a framework to assist researchers and breeders in developing strategies to improve cotton traits by manipulating individual or multiple homeologs.

New Attempts to Inhibit Methicillin-Resistant Staphylococcus aureus Biofilm? A Combination of Daptomycin and Azithromycin.

Objective: To investigate the antibacterial impact of daptomycin and azithromycin in vitro on methicillin-resistant Staphylococcus aureus (MRSA) biofilm. Methods: (1) Measure the strain growth curve and the biofilm formation curve. (2) Determine the minimum inhibitory concentrations (MICs) of daptomycin and azithromycin. (3) Investigate the antibacterial impact of the combination of daptomycin and azithromycin. (4) Perform the evaluation of the intervention impact of antimicrobial agents on MRSA biofilm. (5) Observe the biofilm after intervention with the antibacterial agent. Results: (1) MRSA exhibited three phases: lag phase (0-4 h), logarithmic growth (4-8 h) and stationary phase after 18 h; its biofilm began to form at 6 h, semi-matured at 24 h, and reached maturity after 48 h. (2) The MICs of daptomycin and azithromycin were 8 µg/mL and greater than 256 µg/mL, respectively. (3) The combination of daptomycin and azithromycin has an additive effect on MRSA (Fractional Inhibitory Concentration Index [FICI] 0.625) (FICI = MIC of drug A in combination/MIC of drug A alone + MIC of drug B in combination/MIC of drug B alone). Evaluation criteria: Synergistic effect is considered when FICI ≤ 0.5; additive effect is considered when 0.5 < FICI ≤ 1; irrelevant effect is considered when 1 < FICI ≤ 2; antagonistic effect is considered when FICI > 2). (4) Daptomycin or azithromycin at MICs inhibited not only the growth of planktonic bacteria but also the formation of biofilm. (5) The combination of both, in which group the ratio of live/dead bacteria is low and the biofilm morphology was incomplete, was more productive than monotherapy in against biofilm. Conclusion: Both daptomycin and azithromycin have anti-MRSA biofilm activity, and daptomycin is dominant. The fact that the combination of both can significantly inhibit the further maturation of MRSA biofilm and destroy already formed biofilm demonstrates the superiority of the combination over the monotherapy.

Radix polygoni multiflori protects against hippocampal neuronal apoptosis in diabetic encephalopathy by inhibiting the HDAC4/JNK pathway.

With an poorly characterized pathogenesis, Diabetic encephalopathy (DE), one of the main chronic complications of diabetes, would require further studies. Recent studies have proven that DE developing in conjunction with neuronal apoptosis, which is tightly regulated by a variety of processes and involved with histone acetylation and molecular signaling or so on. Though the histone deacetylase 4 (HDAC4), HDAC5, HDAC7, and HDAC9 form class IIa of the HDAC superfamily have been found participating in multiple neurodegenerative diseases, while JNK signaling pathway activation was hypothesized as a key cause leading to cell apoptosis, the correlation between HDAC4 and JNK signaling pathway remains unknown. Studies have found that Radix Polygoni Multiflori (RPM) contains a variety of ingredients, such as TSG and Emodin, could exert antioxidant effects, scavenge free radicals, inhibit cell apoptosis and provide neuroprotection, but the underlying mechanism has not fully elucidated yet. In the present study, we further explored the mechanism by which RPM improves the cognitive function of diabetic rats. Simultaneously, TSG and Emodin were used to stimulate HT-22 hippocampal neurons treated with high glucose. After RPM extracts or TSG, Emodin treatments, the cognitive functions of DE rats improved while the hippocampal neurons arranged tighter and increased. Meanwhile, the expression level of HAT, HDAC, HDAC4 and JNK signaling pathway and apoptosis related genes were decreased. Our finds indicates that RPM and Emodin would inhibit HDAC4 expression, curb the activation of the JNK pathway, reduce hippocampal neuron apoptosis and ultimately meliorate the cognitive function from diabetes. Additionally, the markedly inhibitory effects of the RPM and Emodin on HAT and HDAC was identified for the first time in this study, which provides a basis for future drug targeting histones acetylation development and application.

Feasibility analysis of flexible bronchoscopy in conjunction with noninvasive ventilation for therapy of hypoxemic patients with Central Airway Obstruction: a retrospective study.

BACKGROUND: Interventional bronchoscopy for hypoxemic patients with central airway obstruction (CAO) is typically performed under general anesthesia. This approach poses remarkable challenge for both bronchoscopist and anesthesiologist. Noninvasive ventilation (NIV) during flexible bronchoscopy (FB) has been successfully used in hypoxemic patients, but rarely in the treatment of hypoxemic patients with CAO. OBJECTIVE: To evaluate the feasibility of therapeutic FB assisted with NIV for therapy of hypoxemic patients with CAO. METHOD: Twenty-nine hypoxemic CAO patients treated with FB from December 2010 to May 2016 in our hospital were retrospectively reviewed, either aided with NIV under sedation (NIV group ) or through artificial airway under general anesthesia (control group). Interventional procedures included balloon dilation, electrocautery and argon plasma coagulation. RESULT: Fifteen patients were enrolled in the NIV group and 14 in the control group. The success rate (93.3% VS 92.9%, p = 1.0), procedure time (60.5 ± 4.2 min VS 67.8 ± 5.6 min, p = 0.31) and oxygenation improvement between the two groups have no significant difference. Less reduction of systolic blood pressure and heart rate during procedure was observed in the NIV group. The NIV group showed shorter admission time before procedure than the control group (35.1 ± 4.6 h VS 55.6 ± 5.6 h, p < 0.01). In addition, procedure fee in the NIV group was significantly less than that in the control group (540.7 ± 62.8$ VS975.4 ± 69.5$, p < 0.0001). CONCLUSION: FB assisted with NIV is a safe, efficient and economic method for therapy of selected hypoxemic patients with CAO.

[Identification and enumeration of dendritic cells in peripheral blood and bone marrow of healthy individuals].

The study was aimed to analyse and enumerate the dendritic cells (DC) subsets in peripheral blood and bone marrow (BM) of healthy individuals in China by using 2 panel 4-color flow cytometry (FCM). The percentage and absolute number of Lin-HLA-DR+CD11chiBDCA1+ myeloid DC (mDC) and Lin-HLA-DR+CD123hiBDCA2+ plasmacytoid DC (pDC) were detected in 35 normal BM (NBM) and 29 normal peripheral blood (NPB), the results were compared with the Lin-HLA-DR+CD11chimDC and Lin-HLA-DR+CD123hi pDC obtained by 3-color FCM. The results indicated that both absolute count of DC subset and relative count of pDC in BM were decreased along with increase of age, the absolute count of DC subset in male BM was higher than that in femoral BM (p<0.05). The DC subsets in NBM and NPB were different whatever by 3 or 4-color cytometric analysis, there were more mDCs than pDCs in PB and the ratio of mDC to pDC was 2.70 and 2.31 respectively. In contrast, pDCs predominated in BM, the ratio of mDC to pDC in BM was 0.90 and 0.71 respectively. The quantity of DC subsets significantly correlated to both frequency (mDC r=0.86; pDC r=0.96, p<0.05) and absolute number (mDC r=0.95; pDC r=0.98, p<0.05) between 3 and 4-color cytometric analysis. The quantity of DC subsets in PB and BM were significantly different, counted by 3 and 4-color cytometric analysis except pDC in PB (p<0.001). The quantity of DC subsets were much higher by 3-color than that by 4-color analysis. Since some Lin-HLA-DR+CD11chimDC and Lin-HLA-DR+CD123hi pDC were BDCA1- and BDCA-2dim/- respectively, that more were in BM than in PB. It is concluded that the DC absolute enumeration is correlated with sample type, gender, age and total nucleated cells (p<0.05). 4-color antibody combination may help to identify the real DC subsets in BM. DC subsets in NBM and NPB are different, that more mDC are in PB whereas more pDC in BM.

[Quantitative analysis of dendritic cell subsets in bone marrow of patients with acute myeloid leukemia].

In order to study the quantity of dendritic cell (DC) subsets of bone marrow in patients with acute myeloid leukemia (AML), the bone marrow aspirate were collected from 77 newly diagnosed AML patients and from 30 healthy persons. The quantity of DC subsets (myeloid dendritic cells, mDC and plasmacytoid dendritic cells, pDC) were detected by flow cytometry and analysed by 3-color and 4-color cytometric gate. Based on the conventional 3-color panel, mDC were identified by Lin-HLA-DR+CD11c+ and pDC were identified by Lin-HLA-DR+CD123+. Based on the 4-color panel, mDC were identified by Lin-HLA-DR+CD11c+ BDCA-1+ and pDC were identified by Lin-HLA-DR+CD123+BDCA-2+. The results showed that a reduction of mDC was found in 74.0% (57/77) and 58.4% (45/77) patients, a reduction of pDC was found in 90.9% (70/77) and 46.8% (36/77) patients respectively by 3-color and 4-color cytometric analysis. Meanwhile an expansion of mDC was showed in 19.5% (15/77) and 22.1% (17/77) patients, an expansion of pDC was showed in 1.3% (1/77) and 27.3% (21/77) patients respectively by 3-color and 4-color cytometric analysis. In subtypes of AML-M2, AML-M3 or AML-M4/5, 81.4%, 100% and 42.1% patients showed mDC decrease and 88.4%, 100% and 89.5% patients showed pDC decrease respectively by 4-color cytometric analysis. It is concluded that the 4-color cytometric gate is better method for detection of mDC and pDC from bone marrow of newly diagnosed AML patients as compared with 3-color cytometric gate, the majority of AML patients showed reduction of mDC and pDC. The percentages of patients with mDC normal or mDC increase in AML-M4/5 subtypes are more than that in AML-M2/3 subtypes, while the pDC does not show difference between AML subtypes.