Suspected coexistence of perianal necrotizing sweet syndrome in chronic myelomonocytic leukemia: A case report.

BACKGROUND: Chronic myelomonocytic leukemia (CMML) complicated with Sweet syndrome (SS) is a rare hematological neoplasm. However, cases of concomitant development of perianal necrotizing SS (NSS) have not been reported. CASE SUMMARY: We report a case of a 49-year-old male patient who underwent sequential procedures for hemorrhoids and perianal abscess. He developed postoperative incision infection and was referred to the department where the authors work. Initially, perianal necrotizing fasciitis secondary to incision infection after perianal abscess surgery was suspected. Despite receiving antibiotic therapy and undergoing surgical debridement, deeper necrotic areas formed in the patient's perianal wounds, accompanied by persistent high fever. Blood and fungal cultures yielded negative results. The final diagnosis was corrected to be CMML with suspected concomitant perianal NSS. CONCLUSION: CMML with perianal NSS is a rare condition, often misdiagnosed as perianal abscess or perianal necrotizing fasciitis. Conventional antibiotic therapy and surgical debridement are ineffective in managing this condition.

Modified Van Assche magnetic resonance imaging-based score for assessing the clinical status of anal fistulas.

The modified Van Assche magnetic resonance imaging (MRI)-based score is a feasible system to assess the clinical status of anal fistulas in Crohn disease. In this study, we evaluated this score's association with clinical status in patients with anal fistulas (AFs).We included all patients with AF who underwent contrast-enhanced pelvic MRI and surgery between January 2011 and December 2016. The score was evaluated retrospectively preoperatively and 1, 3, and 6 months postoperatively. Univariate and multivariate analyses of the risk factors for AF recurrence were also performed.We retrospectively analyzed data for 104 patients. Twelve (11.5%) patients developed AF recurrence. We classified patients' preoperative clinical status into three grades: 52 (50.0%) grade A, 31 (29.8%) grade B, and 21 (20.2%) grade C. The preoperative MRI-based score was significantly correlated with patients' preoperative clinical status grade (Pearson correlation: 0.547; P < .001). The 3 preoperative clinical status grades showed significant (F = 23.303, P < .001) tendencies for associations with lower respective MRI-based scores. The incidence of AF recurrence decreased with the MRI-based score to 1-month postoperatively, then gradually increased (F = 60.863, P = .000). Long duration of disease, prior interventions, and high MRI-based score were independent risk factors for AF recurrence.The MRI-based score objectively assessed the clinical status and disease activity of patients with AFs, with a high score being associated with severe clinical status and long recovery time.

Effect of lateral internal sphincterotomy in patients undergoing excisional hemorrhoidectomy.

BACKGROUND: Excisional hemorrhoidectomy (EH) is the major surgical option for high-grade symptomatic hemorrhoids, but it has some shortcomings, especially postoperative pain. This study was performed to assess the effect of lateral internal sphincterotomy (LIS) in patients undergoing excisional hemorrhoidectomy. METHODS: A systematic literature search (Medline, Embase, Cochrane Library, Science Citation Index, Science Direct, Springer Link, Ovid Journals, and EBSCO) was performed to identify all eligible articles. Randomized controlled trials (RCTs) published until July 7, 2017 comparing EH combined with LIS (experimental group) with EH only (control group) were eligible for inclusion. The primary outcome of interest was postoperative pain. RESULTS: Ten RCTs involving 1560 patients were identified for inclusion. The pooled analysis revealed that patients undergoing EH and LIS were associated with lower pain score [standardized mean difference (SMD), -0.75; 95% confidence interval (CI), -1.14 to -0.36; z = 3.76; P = .0002] and resting anal pressure [odds ratio (OR), -17.19; 95% CI, -25.66 to -8.72; z = 3.98; P < .0001], and lower incidence of anal stricture (OR, 0.12; 95% CI, 0.03-0.53; z = 2.85; P = .004). However, the differences of urinary retention, bleeding and length of hospital stay were similar between the 2 methods. CONCLUSION: Our meta-analysis suggests that LIS effectively relieves postoperative pain and reduces patient's postoperative analgesic requirements. LIS also reduces the incidence of anal stenosis but increases the incidence of fecal incontinence.

[Hyperspectral Technique for Estimating the Shelf-Lives of Fresh Spinach Leaves Covered with Film].

In order to prolong the shelf-life of fruits and vegetables, plastic films have been covered on them to improve water retention and keep external bacteria away. It is of great significance to estimate the quality of packaged fruits and vegetables accurately by predicting the shelf-life of them. In this research, hyperspectral technology combined with chemometric methods were employed to estimate the shelf-life of fresh spinach leaves in the same environment. Hyperspectral data covering the range of Vis-NIR (380～1 030 nm) and NIR (874～1 734 nm) were acquired from 300 spinach leaves (75 dishs) which were stored in 4 ℃ among 5 periods (0 d, 2 d, 4 d, 6 d, 8 d). Meanwhile, the chlorophyll contents of all spinach leaves were determined. The mean spectra of 300 spinach leaves (200 leaves in training set and 100 leaves in prediction set) were extracted. And then, principal component analysis (PCA) on the training set of 200 spectra from 5 periods of shelf-life displayed apparent cluster. Partial least-squares discriminant analysis (PLS-DA) models were established according to spectral datas and the virtual levels that we ascribed to the different storage periods previously. The total discriminant accuracy rates of prediction set were 83% (VIS-NIR) and 81% (NIR), respectively. The result indicated that the classification and prediction on the shelf-life of fresh spinach can be realized with hyperspectral technology combined with chemometric methods, which offered a theoretical guidance to evaluate the quality of packaged spinach for consumers, and provided technical supports for the development of instruments used for testing the shelf-life of fruits and vegetables in further study.

[Discriminate the Rape Sclerotinia at Early Stage Based on Confocal Raman Spectroscopy].

Oilseed rape(Brassica napus L. ) is a principal source of edible oil for human consumption and it feeds livestock as a by product with high energy and protein. However, oilseed plants often suffer from the invasion of various diseases, which could affect the yield and quality of the rapeseeds. Rape sclerotinia rot caused by the fungus sclerotinia sclerotiorum (Lib. ) de Bary may severely affect the growth of oilseed rape. Therefore, searching non-invasive detection methods of detection plant disease at early stage is crucial for monitoring growing conditions of crops. Confocal Raman spectroscopy in the region of 500～2 000 cm(-1) coupled with chemometrics methods were employed to discriminate the rape sclerotinia disease at early stage on the oilseed rape leaves. A total of 60 samples(30 healthy plant leaves and 30 infected leaves) were used to acquire the Raman spectra and wavelet transform was applied to remove the fluorescence background. Regression coefficients of the partial least squares-discriminant analysis(PLS-DA) were used to select the 8 characteristic peaks based on the whole Raman spectra. 983，1 001, 1 205, 1 521, 1 527, 1 658, 1 670 and 1 758 cm(-1) were employed to establish PLS-DA discriminate models and recognition accuracy was 100%. The results showed Raman spectra combined with chemometrics method is promising for detecting rape sclerotinia infection in the oilseed rape leaves at early stage. This study provided a theoretical reference for researching the interaction between the fungus and plants and early detecting of disease infection.

Detection of Fungus Infection on Petals of Rapeseed (Brassica napus L.) Using NIR Hyperspectral Imaging.

Infected petals are often regarded as the source for the spread of fungi Sclerotinia sclerotiorum in all growing process of rapeseed (Brassica napus L.) plants. This research aimed to detect fungal infection of rapeseed petals by applying hyperspectral imaging in the spectral region of 874-1734 nm coupled with chemometrics. Reflectance was extracted from regions of interest (ROIs) in the hyperspectral image of each sample. Firstly, principal component analysis (PCA) was applied to conduct a cluster analysis with the first several principal components (PCs). Then, two methods including X-loadings of PCA and random frog (RF) algorithm were used and compared for optimizing wavebands selection. Least squares-support vector machine (LS-SVM) methodology was employed to establish discriminative models based on the optimal and full wavebands. Finally, area under the receiver operating characteristics curve (AUC) was utilized to evaluate classification performance of these LS-SVM models. It was found that LS-SVM based on the combination of all optimal wavebands had the best performance with AUC of 0.929. These results were promising and demonstrated the potential of applying hyperspectral imaging in fungus infection detection on rapeseed petals.

[Study on Soil Elements Detection with Laser-Induced Breakdown Spectroscopy: A Review].

Laser-induced breakdown spectroscopy (LIBS), as a kind of atomic emission spectroscopy, has been considered to be a future new tool for chemical analysis due to its unique features, such as no need of sample preparation, stand-off or remote analysis. What's more it can achieve fast and multi-element analysis. Therefore, LIBS technology is regarded as a future "SurperStar" in the field of chemical analysis and green analytical techniques. At present, rapid and accurate detection and prevention of soil contamination (mainly in pollutants of heavy metals and organic matter) is deemed to be a concerned and serious central issue in modern agriculture and agricultural sustainable development. In this paper, the reseach achievements and trends of soil elements detection based on LIBS technology were being reviewed. The structural composition and foundmental of LIBS system is first briefly introduced. And the paper offers a review of on LIBS applications and fruits including the detection and analysis of major element, nutrient element and heavy metal element. Simultaneously, some studies on soil related metials and fields are briefly stated. The research tendency and developing prospects of LIBS in soil detection are presented at last.

Laser-Induced Breakdown Spectroscopy Coupled with Multivariate Chemometrics for Variety Discrimination of Soil.

The aim of this work was to analyze the variety of soil by laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics methods. 6 certified reference materials (CRMs) of soil samples were selected and their LIBS spectra were captured. Characteristic emission lines of main elements were identified based on the LIBS curves and corresponding contents. From the identified emission lines, LIBS spectra in 7 lines with high signal-to-noise ratio (SNR) were chosen for further analysis. Principal component analysis (PCA) was carried out using the LIBS spectra at 7 selected lines and an obvious cluster of 6 soils was observed. Soft independent modeling of class analogy (SIMCA) and least-squares support vector machine (LS-SVM) were introduced to establish discriminant models for classifying the 6 types of soils, and they offered the correct discrimination rates of 90% and 100%, respectively. Receiver operating characteristic (ROC) curve was used to evaluate the performance of models and the results demonstrated that the LS-SVM model was promising. Lastly, 8 types of soils from different places were gathered to conduct the same experiments for verifying the selected 7 emission lines and LS-SVM model. The research revealed that LIBS technology coupled with chemometrics could conduct the variety discrimination of soil.

Hyperspectral Imaging for Determining Pigment Contents in Cucumber Leaves in Response to Angular Leaf Spot Disease.

Hyperspectral imaging technique was employed to determine spatial distributions of chlorophyll (Chl), and carotenoid (Car) contents in cucumber leaves in response to angular leaf spot (ALS). Altogether, 196 hyperspectral images of cucumber leaves with five infection severities of ALS were captured by a hyperspectral imaging system in the range of 380-1,030 nm covering 512 wavebands. Mean spectrum were extracted from regions of interest (ROIs) in the hyperspectral images. Partial least square regression (PLSR) models were used to develop quantitative analysis between the spectra and the pigment contents measured by biochemical analyses. In addition, regression coefficients (RCs) in PLSR models were employed to select important wavelengths (IWs) for modelling. It was found that the PLSR models developed by the IWs provided the optimal measurement results with correlation coefficient (R) of prediction of 0.871 and 0.876 for Chl and Car contents, respectively. Finally, Chl and Car distributions in cucumber leaves with the ALS infection were mapped by applying the optimal models pixel-wise to the hyperspectral images. The results proved the feasibility of hyperspectral imaging for visualizing the pigment distributions in cucumber leaves in response to ALS.

[Associations between health-promoting lifestyle and suboptimal health status in Guangdong: a cross sectional study].

OBJECTIVE: To investigate associations between health-promoting lifestyle and suboptimal health status (SHS) in the population of Guangdong province. METHODS: A cross-sectional survey was conducted in a clustered sample of 24 159 individuals aged 12-80 years from 2012 to 2013. Health-promoting lifestyle was assessed via the Health-Promoting Lifestyle Profile (HPLP-II), and SHS was evaluated using the medical examination report and Sub-health Measurement Scale V1.0 (SHMS V1.0). RESULTS: Of the 24159 participants, subjects with SHS (46.0%) and disease status (35.2%) accounted for a much higher percentage than healthy subjects (18.8%). Regression analyses revealed a significant association between health status and healthy lifestyle (P<0.001). Unhealthy lifestyle was an important risk factor for SHS and disease, especially the former. Compared with the participants with a healthy lifestyle (minimal exposure), after demographic adjustment, subjects with a 'poor' lifestyle (maximal exposure) were at a 43 times higher risk of developing SHS (OR: 42.825, 95% CI: 30.567-59.997), those with a general lifestyle were at a 21 times higher risk of SHS (OR: 21.072, 95%CI: 17.258-25.729), and those with a suboptimal lifestyle had a 4 times higher risk (OR: 4.085, 95%CI: 3.352-4.979). In the general population, the major risk factors for SHS included poor stress management, poor self-actualization, inactive exercise and poor interpersonal relationship. CONCLUSION: s Unhealthy lifestyles are significantly related to an increased risk of SHS. Intervention of unhealthy lifestyles, controlling the risk factors of SHS, and rigorous management of the time window of SHS are necessary to promote the heath status.

[Effect of health-promoting lifestyle on outcomes of suboptimal health status].

OBJECTIVE: To determine evaluate the effect of health-promoting lifestyle on the outcomes of suboptimal health status (SHS). METHODS: A prospective population cohort was conducted by consecutively enrolling 5676 college students who took routine health examination from March to May 2013. The participants were assessed for baseline health status and lifestyle and 2972 participants with SHS were followed up for 1.5 years. Exposure was defined as an unhealthy lifestyle. The health-promoting lifestyle was assessed via the Health-promoting Lifestyle Profile (HPLP-II). SHS was evaluated using the medical examination report and Sub-health Measurement Scale V1.0 (SHMS V1.0). RESULTS: Among the 2972 students with SHS, 422 showed recovery of the healthy status at 1.5 year follow-up, 579 showed progression into disease conditions, and 1971 remained in SHS. The participants with recovered health status presented with significant increase of SHMS V1.0 scores by 8.75∓6.95 points compared to the baseline assessment (t=-2.14, P=0.000) in physiological, psychological and social dimensions; they also showed a marked improvement of HPLP-II scores by 14.73 points in 6 dimensions (t=-15.34, P=0.000). Multivariable regression analyses with adjusted demographic variables revealed a significant association between health status and health-promoting lifestyle (P<0.05). Compared with a healthy lifestyle (minimal exposure), a 'poor' lifestyle (the highest level of exposure) was associated with a 30 times higher risk of developing SHS (OR: 30.598, 95% CI: 3.928-238.331), while a 'moderate' lifestyle (a relatively high-level exposure) had a 24 times higher risk of SHS (OR: 23.988, 95%CI: 14.695-39.158), and a suboptimal lifestyle had a nearly 4 times higher risk of SHS (OR: 4.306, 95%CI: 2.767-6.702). CONCLUSION: s SHS may evolve into either a healthy or a disease condition. A unhealthy lifestyle is the important risk factor contributing to the progression of SHS into a disease condition, suggesting the importance of intervention of unhealthy lifestyles in promoting good health.

Hyperspectral Imaging Coupled with Random Frog and Calibration Models for Assessment of Total Soluble Solids in Mulberries.

Chemometrics methods coupled with hyperspectral imaging technology in visible and near infrared (Vis/NIR) region (380-1030 nm) were introduced to assess total soluble solids (TSS) in mulberries. Hyperspectral images of 310 mulberries were acquired by hyperspectral reflectance imaging system (512 bands) and their corresponding TSS contents were measured by a Brix meter. Random frog (RF) method was used to select important wavelengths from the full wavelengths. TSS values in mulberry fruits were predicted by partial least squares regression (PLSR) and least-square support vector machine (LS-SVM) models based on full wavelengths and the selected important wavelengths. The optimal PLSR model with 23 important wavelengths was employed to visualise the spatial distribution of TSS in tested samples, and TSS concentrations in mulberries were revealed through the TSS spatial distribution. The results declared that hyperspectral imaging is promising for determining the spatial distribution of TSS content in mulberry fruits, which provides a reference for detecting the internal quality of fruits.

[Application of Hyperspectral Imaging for Visualization of Nitrogen Content in Pepper Leaf with Different Positions].

In order to estimate pepper plant growth rapidly and accurately, hyperspectral imaging technology combined with chemometrics methods were employed to realize visualization of nitrogen content (NC) distribution. First, pepper leaves were picked up with the leaf number based on different leaf positions, and hyperspectral data of these leaves were acquired. Then, SPAD and NC value of leaves were measured, respectively. After acquirement of pepper leaves' spectral information, random-frog (RF) algorithm was chosen to extract characteristic wavelengths. Finally, five characteristic wavelengths were selected respectively, and then those characteristic wavelengths and full spectra were used to establish partial least squares regression (PLSR) models, respectively. As a result, SPAD predicted model had an excellent performance of R(C) = 0.970, R(CV) = 0.965, R(P) = 0.934, meanwhile evaluation parameters of NC predicted model were R(C) = 0.857, R(CV) = 0.806, R(P) = 0.839. Lastly, according to the optimal models, SPAD and NC of each pixel in hyperspectral images of pepper leaves were calculated and their distribution was mapped. In fact, SPAD in plant can reflect the NC. In this research, the change trend of both was similar, so the conclusions of this research were proved to be corrected. The results revealed that it was feasible to apply hyperspectral imaging technology for mapping SPAD and NC in pepper leaf, which provided a theoretical foundation for monitoring plant growth and distribution of nutrients.

[Detection of Hawthorn Fruit Defects Using Hyperspectral Imaging].

Hyperspectral imaging technology covered the range of 380-1000 nm was employed to detect defects (bruise and insect damage) of hawthorn fruit. A total of 134 samples were collected, which included damage fruit of 46, pest fruit of 30, injure and pest fruit of 10 and intact fruit of 48. Because calyx · s⁻¹ tem-end and bruise/insect damage regions offered a similar appearance characteristic in RGB images, which could produce easily confusion between them. Hence, five types of defects including bruise, insect damage, sound, calyx, and stem-end were collected from 230 hawthorn fruits. After acquiring hyperspectral images of hawthorn fruits, the spectral data were extracted from region of interest (ROI). Then, several pretreatment methods of standard normalized variate (SNV), savitzky golay (SG), median filter (MF) and multiplicative scatter correction (MSC) were used and partial least squares method(PLS) model was carried out to obtain the better performance. Accordingly to their results, SNV pretreatment methods assessed by PLS was viewed as best pretreatment method. Lastly, SNV was chosen as the pretreatment method. Spectral features of five different regions were combined with Regression coefficients(RCs) of partial least squares-discriminant analysis (PLS-DA) model was used to identify the important wavelengths and ten wavebands at 483, 563, 645, 671, 686, 722, 777, 819, 837 and 942 nm were selected from all of the wavebands. Using Kennard-Stone algorithm, all kinds of samples were randomly divided into training set (173) and test set (57) according to the proportion of 3:1. And then, least squares-support vector machine (LS-SVM) discriminate model was established by using the selected wavebands. The results showed that the discriminate accuracy of the method was 91.23%. In the other hand, images at ten important wavebands were executed to Principal component analysis (PCA). Using "Sobel" operator and region growing algrorithm "Regiongrow", the edge and defect feature of 86 Hawthorn could be recognized. Lastly, the detect precision of bruised, insect damage and two-defect samples is 95.65%, 86.67% and 100%, respectively. This investigation demonstrated that hyperspectral imaging technology could detect the defects of bruise, insect damage, calyx, and stem-end in hawthorn fruit in qualitative analysis and feature detection which provided a theoretical reference for the defects nondestructive detection of hawthorn fruit.

Hyperspectral imaging for mapping of total nitrogen spatial distribution in pepper plant.

Visible/near-infrared (Vis/NIR) hyperspectral imaging was employed to determine the spatial distribution of total nitrogen in pepper plant. Hyperspectral images of samples (leaves, stems, and roots of pepper plants) were acquired and their total nitrogen contents (TNCs) were measured using Dumas combustion method. Mean spectra of all samples were extracted from regions of interest (ROIs) in hyperspectral images. Random frog (RF) algorithm was implemented to select important wavelengths which carried effective information for predicting the TNCs in leaf, stem, root, and whole-plant (leaf-stem-root), respectively. Based on full spectra and the selected important wavelengths, the quantitative relationships between spectral data and the corresponding TNCs in organs (leaf, stem, and root) and whole-plant (leaf-stem-root) were separately developed using partial least-squares regression (PLSR). As a result, the PLSR model built by the important wavelengths for predicting TNCs in whole-plant (leaf-stem-root) offered a promising result of correlation coefficient (R) for prediction (RP = 0.876) and root mean square error (RMSE) for prediction (RMSEP = 0.426%). Finally, the TNC of each pixel within ROI of the sample was estimated to generate the spatial distribution map of TNC in pepper plant. The achievements of the research indicated that hyperspectral imaging is promising and presents a powerful potential to determine nitrogen contents spatial distribution in pepper plant.

[Study on SPAD visualization of pumpkin leaves based on hyperspectral imaging technology].

Visible/near-infrared (380 approximately 1 030 nm) hyperspectral imaging technique was used to realize SPAD visualization of pumpkin leaves in the present study. Downy mildew could be diagnosed rapidly according to significant positive correlation between downy mildew epidemic and chlorophyll content. Leaves uninfected and infected with different level downy mildew were used to acquire hyperspectral images and extract spectral information. Competitive adaptive reweighted sampling (CARS) was applied to select optimal wavelengths and finally 10 optimal wavelengths were obtained. Partial least squares regression (PLSR) was employed to establish SPAD prediction model. Results showed that, through the analysis of calibration of 48 samples and prediction of 23 samples, CARS-PLSR could obtain good results with Rc= 0. 918, RMSECV= 3. 932; Rcv- 0. 846, RMSECV = 5. 254; Rp = 0. 881, and RMSEP= 3. 714. Regression model was gained based on the relationship between SPAD and spectral of pumpkin leaves. While SPAD of each pixel was calculated with PLSR regression equation, then SPAD distribution map of pumpkin was visualized using imaging processing technology. Final downy mildew infection could be diagnosed based on SPAD distribution map. This study provided a theoretical reference for effective monitoring plant growth and downy mildew epidemic.

[Study on identification the crack feature of fresh jujube using hyperspectral imaging].

Crack is one of the most important indicators to evaluate the quality of fresh jujube. Crack not only accelerates the decay of fresh jujube, but also diminishes the shelf life and reduces the economic value severely. In this study, the potential of hyperspectral imaging covered the range of 380 - 1030 nm was evaluated for discrimination crack feature (location and area) of fresh jujube. Regression coefficients of partial least squares regression (PLSR), successive projection analysis (SPA) and principal component analysis (PCA) based full-bands image were adopted to extract sensitive bands of crack of fresh jujube. Then least-squares support vector machine (LS-SVM) discriminant models using the selected sensitive bands for calibration set (132 samples)" were established for identification the prediction set (44 samples). ROC curve was used to judge the discriminant models of PLSR-LS-SVM, SPA-LS-SVM and PCA-LS-SVM which are established by sensitive bands of crack of fresh jujube. The results demonstrated that PLSR-LS-SVM model had an optimal effect (area=1, std=0) to discriminate crack feature of fresh jujube. Next, images corresponding to five sensitive bands (467, 544, 639, 673 and 682 nm) selected by PLSR were executed to PCA. Finally, the image of PC4 was employed to identify the location and area of crack feature through imaging processing. The results revealed that hyperspectral imaging technique combined with image processing could achieve the qualitative discrimination and quantitative identification of crack feature of fresh jujube, which provided a theoretical reference and basis for develop instrument of discrimination of crack of jujube in further work.

Comparison of direct boiling method with commercial kits for extracting fecal microbiome DNA by Illumina sequencing of 16S rRNA tags.

Low cost and high throughput capacity are major advantages of using next generation sequencing (NGS) techniques to determine metagenomic 16S rRNA tag sequences. These methods have significantly changed our view of microorganisms in the fields of human health and environmental science. However, DNA extraction using commercial kits has shortcomings of high cost and time constraint. In the present study, we evaluated the determination of fecal microbiomes using a direct boiling method compared with 5 different commercial extraction methods, e.g., Qiagen and MO BIO kits. Principal coordinate analysis (PCoA) using UniFrac distances and clustering showed that direct boiling of a wide range of feces concentrations gave a similar pattern of bacterial communities as those obtained from most of the commercial kits, with the exception of the MO BIO method. Fecal concentration by boiling method affected the estimation of α-diversity indices, otherwise results were generally comparable between boiling and commercial methods. The operational taxonomic units (OTUs) determined through direct boiling showed highly consistent frequencies with those determined through most of the commercial methods. Even those for the MO BIO kit were also obtained by the direct boiling method with high confidence. The present study suggested that direct boiling could be used to determine the fecal microbiome and using this method would significantly reduce the cost and improve the efficiency of the sample preparation for studying gut microbiome diversity.

Anti-fatigue activity of polysaccharides extract from Radix Rehmanniae Preparata.

The anti-fatigue effects of the Radix Rehmanniae Preparata polysaccharides (RRPP) were studied in mice. The RRPP were orally administered at doses of 50, 100 and 200 mg/kg for 4 weeks and the anti-fatigue activity was evaluated using a weight-loaded swimming test, along with the determination of serum urea nitrogen (SUN), hepatic glycogen and blood lactic acid (BLA) contents. The results showed that there was no significant difference in the body weight of mice in the three RRPP groups compared with the negative control group during initial, intermediate and terminal stages in the experiment (p>0.05). The ratio of exhausting swimming time was obviously increased 31.48% (p<0.05) and 61.51% (p<0.01) in the middle-dose group and the high-dose RRPP group, respectively. The BLA and SUN levels were decreased in middle-dose and high-dose RRPP groups (p<0.01). Hepatic glycogen level was increased in three RRPP treated groups (p<0.01). Therefore, RRPP may be responsible for the pharmacological effect of anti-fatigue of Radix Rehmanniae Preparata. The mechanism was related to the increase of the storage of hepatic glycogen and the decrease of the accumulation of SUN and BLA.

Chinese herbal medicine liu jun zi tang and xiang sha liu jun zi tang for functional dyspepsia: meta-analysis of randomized controlled trials.

Objectives. To assess the efficacy and safety of Liu Jun Zi Tang (LJZT) and Xiang Sha Liu Jun Zi Tang (XSLJZT) for treating functional dyspepsia. Methods. Literature searches were carried out on Medline database, Cochrane Library, CNKI database, Chinese Biomedical Literature database, Wanfang database, and VIP database up to July 2012. Hand search for further references was conducted. Study selection, data extraction, quality assessment, and data analyses were performed according to the Cochrane standards. Results. Fifteen publications in total were suitable for inclusion. There was evidence that LJZT compared with prokinetic drugs increased symptom improvement (odds ratio 1.96, 95% CI 1.15 to 3.36). There was also evidence that XSLJZT compared with prokinetic drugs increased symptom improvement (odds ratio 2.63, 95% CI 1.72 to 4.03). No adverse events were reported in LJZT or XSLJZT group in any of these randomized controlled trials. Conclusion. LJZT and XSLJZT might be more effective compared with prokinetic drugs in the treatment of functional dyspepsia, and no side effects are identified in the included trials. However, due to poor methodological quality in the majority of included studies, the potential benefit from LJZT and XSLJZT need to be confirmed in rigorously designed, multicentre, and large-scale trials.