Diagnostic performance of radiomics for predicting osteoporosis in adults: a systematic review and meta-analysis.

This study aimed to assess the diagnostic accuracy of radiomics for predicting osteoporosis and the quality of radiomic studies. The study protocol was prospectively registered on PROSPERO (CRD42023425058). We searched PubMed, EMBASE, Web of Science, and Cochrane Library databases from inception to June 1, 2023, for eligible articles that applied radiomic techniques to diagnosing osteoporosis or abnormal bone mass. Quality and risk of bias of the included studies were evaluated with radiomics quality score (RQS), METhodological RadiomICs Score (METRICS), and Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tools. The data analysis utilized the R program with mada, metafor, and meta packages. Ten retrospective studies with 5926 participants were included in the systematic review and meta-analysis. The overall risk of bias and applicability concerns for each domain of the studies were rated as low, except for one study which was considered to have a high risk of flow and time bias. The mean METRICS score was 70.1% (range 49.6-83.2%). There was moderate heterogeneity across studies and meta-regression identified sources of heterogeneity in the data, including imaging modality, feature selection method, and classifier. The pooled diagnostic odds ratio (DOR) under the bivariate random effects model across the studies was 57.22 (95% CI 27.62-118.52). The pooled sensitivity and specificity were 87% (95% CI 81-92%) and 87% (95% CI 77-93%), respectively. The area under the summary receiver operating characteristic curve (AUC) of the radiomic models was 0.94 (range 0.8 to 0.98). The results supported that the radiomic techniques had good accuracy in diagnosing osteoporosis or abnormal bone mass. The application of radiomics in osteoporosis diagnosis needs to be further confirmed by more prospective studies with rigorous adherence to existing guidelines and multicenter validation.

Temperature fluctuations during embryo transfer can be mitigated by optimizing transfer protocol.

RESEARCH QUESTION: What impact do variations in embryo transfer catheter loading and movement procedures have on temperature and pH fluctuations during embryo transfer? DESIGN: Mock embryo transfers were conducted to test the impact of air flow/movement, use of catheter coverings, and the type of workstation used for catheter loading on catheter temperature. A thermocouple probe inserted into the tip of the outer catheter or taped to the exterior of the inner catheter recorded temperature within the catheter every 5 s from time of mock embryo loading (TL) to 60 s (TL + 60 s) or from the start of transit (TT). Fluctuations in culture medium pH in embryo transfer dishes were monitored. RESULTS: The rate of cooling during transit was faster (all P < 0.05) when catheters were uncovered compared with all covering methods tested. This resulted in a lower catheter temperature at TL + 20 s (28.43 ± 0.30 °C) compared with catheters covered by plastic tubing (31.4 ± 0.30 °C), paper (31.0 ± 0.26 °C) or paper + thumb (31.1 ± 0.78 °C; all P ≤ 0.05). Temperature was maintained more effectively when catheters were loaded in a crib compared with a heated stage, until initiation of transit, when the rate of temperature decrease was similar. Culture medium pH increased more rapidly when embryo transfer dishes remained on a heated stage during the procedure compared with in an open crib. CONCLUSIONS: Temperature loss during the embryo transfer procedure can be mitigated by reducing the transit time and using catheter coverings. Use of a crib for catheter loading only improved temperature stability while the catheter remained in the crib, not during transit, and reduced pH fluctuations during the procedure.

Quality study of animal-derived traditional Chinese medicinal materials based on spectral technology: Calculus bovis as a case.

INTRODUCTION: Calculus bovis (C. bovis) is a typical traditional Chinese medicine (TCM) derived from animals, which has a remarkable curative effect and high price. OBJECTIVES: Rapid identification of C. bovis from different types was realized based on spectral technology, and a rapid quantitative analysis method for the main quality control indicator bilirubin was established. METHODS: We conducted a supervised and unsupervised pattern recognition study on 44 batches of different types of C. bovis by five spectral pretreatment methods. Three variable selection methods were used to extract the essential information, and the partial least squares regression (PLSR) quantitative model of bilirubin by near-infrared (NIR) spectroscopy was constructed. RESULTS: The partial least squares discriminant analysis (PLS-DA) model could achieve 100% accuracy in identifying different types of C. bovis. The R2 of the NIR quantitative model was 0.979, which is close to 1, and the root mean square error of calibration (RMSEC) was 2.3515, indicating the good prediction ability of the model. CONCLUSION: The study was carried out to further improve the basic data of quality control of C. bovis and help the high-quality development of TCM derived from animals.

Study on quality analysis of different species of Coptidis rhizome based on fingerprint-effect relationship.

INTRODUCTION: The quality evaluation of Coptidis rhizome (CR) is attributed to the origin and processing method, and this strategy of ignoring the bioactive components usually leads to biased quality analysis, which is difficult to indicate the clinical efficacy. OBJECTIVES: In order to evaluate the quality level of different species of CR, we collected 20 batches of CR and investigated the fingerprint-effect relationship. METHODS: High-performance liquid chromatography (HPLC) fingerprints of CR were established, and the fingerprint-effect relationship was explored using cluster analysis, principal component analysis, Pearson correlation analysis, grey relation analysis, and partial least squares regression. RESULTS: We have identified a total of 10 common peaks (1-10) with similarity scores above 0.96. The study on the relationship between spectra and potency further showed that the contents of peaks 8, 9, and 10 are potential key components. And based on a previous study, a method of one measurement and multiple evaluations of CR was established to achieve the goal of simplifying the analytical process and reducing costs. CONCLUSION: Through a combination of fingerprint analysis, antioxidant activity evaluation, fingerprint-efficacy relationship analysis, and simultaneous quantification of multiple components, a CR quality control index and method have been selected and established, which can also provide a more comprehensive quality evaluation for traditional Chinese medicine.

Temporal-Quality Ensemble Technique for Handling Image Blur in Packaging Defect Inspection.

Despite achieving numerous successes with surface defect inspection based on deep learning, the industry still faces challenges in conducting packaging defect inspections that include critical information such as ingredient lists. In particular, while previous achievements primarily focus on defect inspection in high-quality images, they do not consider defect inspection in low-quality images such as those containing image blur. To address this issue, we proposed a noble inference technique named temporal-quality ensemble (TQE), which combines temporal and quality weights. Temporal weighting assigns weights to input images by considering the timing in relation to the observed image. Quality weight prioritizes high-quality images to ensure the inference process emphasizes clear and reliable input images. These two weights improve both the accuracy and reliability of the inference process of low-quality images. In addition, to experimentally evaluate the general applicability of TQE, we adopt widely used convolutional neural networks (CNNs) such as ResNet-34, EfficientNet, ECAEfficientNet, GoogLeNet, and ShuffleNetV2 as the backbone network. In conclusion, considering cases where at least one low-quality image is included, TQE has an F1-score approximately 17.64% to 22.41% higher than using single CNN models and about 1.86% to 2.06% higher than an average voting ensemble.

Reengineering Indoor Air Quality Monitoring Systems to Improve End-User Experience.

This paper presents an indoor air quality (IAQ) monitoring system designed for a better end-user experience. The monitoring system consists of elements, from the monitoring sensor to the monitoring interface, designed and implemented by the research team, especially for the proposed monitoring system. The monitoring solution is intended for users who live in houses without automatic ventilation systems. The air quality sensor is designed at a minimum cost and complexity to allow multi-zone implementation without significant effort. The user interface uses a spatial graphic representation that facilitates understanding areas with different air quality levels. Presentation of the outdoor air quality level supports the user's decision to ventilate a space. An innovative element of the proposed monitoring interface is the real-time forecast of air quality evolution in each monitored space. The paper describes the implementation of an original monitoring solution (monitoring device, Edge/Cloud management system, innovative user monitoring interface) and presents the results of testing this system in a relevant environment. The research conclusions show the proposed solution's benefits in improving the end-user experience, justified both by the technical results obtained and by the opinion of the users who tested the monitoring system.

A Direct Comparison of rAAV5 Variants Derived from the Baculovirus Expression System Using LC-MS Workflows Demonstrates Key Differences in Overall Production Yield, Product Quality and Vector Efficiency.

Gene therapy holds great promise for the treatment of severe diseases, and adeno-associated virus (AAV) vectors have emerged as valuable tools in this field. However, challenges such as immunogenicity and high production costs complicate the commercial viability of AAV-based therapies. To overcome these barriers, improvements in production yield, driven through the availability of robust and sensitive characterization techniques that allow for the monitoring of critical quality attributes to deepen product and process understanding are crucial. Among the main attributes affecting viral production and performance, the ratio between empty and full capsids along with capsid protein stoichiometry are emerging as potential parameters affecting product quality and safety. This study focused on the production of AAV vectors using the baculovirus expression vector system (BEVS) in Sf9 cells and the complete characterization of AAV5 variants using novel liquid chromatography and mass spectrometry techniques (LC-MS) that, up to this point, had only been applied to reference commercially produced virions. When comparing virions produced using ATG, CTG or ACG start codons of the cap gene, we determined that although ACG was the most productive in terms of virus yield, it was also the least effective in transducing mammalian cells. This correlated with a low VP1/VP2 ratio and a higher percentage of empty capsids. Overall, this study provides insights into the impact of translational start codon modifications during rAAV5 production using the BEVS, the associated relationship with capsid packaging, capsid protein stoichiometry and potency. The developed characterization workflow using LC-MS offers a comprehensive and transferable analysis of AAV-based gene therapies, with the potential to aid in process optimization and facilitate the large-scale commercial manufacturing of these promising treatments.

Effects of Torulaspora delbrueckii and Saccharomyces cerevisiae Co-Fermentation on the Physicochemical and Flavor Compounds of Huaniu Apple Cider.

The effects of different fermentation methods utilizing Torulaspora delbrueckii 1004 and Saccharomyces cerevisiae 32169 on the physicochemical properties, organic acid content, polyphenol and flavonoid concentrations, antioxidant activity, and volatile aroma compounds of Huaniu apple cider were investigated in this study. Employing methods of single inoculation, co-inoculation, and sequential inoculation, it was found that sequential fermentation exhibited strong fermentative power in the initial stages, effectively reducing the content of soluble solids and achieving a balanced composition of malic, succinic, and citric acids while maintaining a lower titratable acidity. Sequential inoculation was observed to significantly enhance the total polyphenols and flavonoids, as well as the antioxidant capacity (p < 0.05). Specifically, in the synthesis of volatile aroma compounds, sequential inoculation significantly enhanced the richness and diversity of the Huaniu apple cider's aromas, particularly in terms of the concentration of ester compounds (p < 0.05). Principal component analysis further confirmed the superiority of sequential inoculation in terms of aroma component diversity and richness. The findings of this study suggest that sequential inoculation of fermentation with non-Saccharomyces and S. cerevisiae is an effective strategy for optimizing the flavor characteristics of Huaniu apple cider, offering valuable theoretical support and practical guidance for enhancing cider quality and fostering the development of new products.

Study on Quality Characteristic of Chebulae Fructus and Its Adulterants and Degradation Pathway of Hydrolyzable Tannins.

Chebulae Fructus (CF) is known as one of the richest sources of hydrolyzable tannins (HTs). In this study, ultra-performance liquid chromatography coupled with a photodiode array detector method was established for simultaneous determination of the 12 common phenolcarboxylic and tannic constituents (PTCs). Using this method, quantitative analysis was accomplished in CF and other four adulterants, including Terminaliae Belliricae Fructus, Phyllanthi Fructus, Chebulae Fructus Immaturus, and Canarii Fructus. Based on a quantitative analysis of the focused compounds, discrimination of CF and other four adulterants was successfully accomplished by hierarchical cluster analysis and principal component analysis. Additionally, the total contents of the 12 compounds that we focused on in this study were unveiled as 148.86 mg/g, 96.14 mg/g, and 18.64 mg/g in exocarp, mesocarp, and endocarp and seed of CF, respectively, and PTCs were witnessed to be the most abundant in the exocarp of CF. Noticeably, the HTs (chebulagic acid, chebulanin acid, chebulinic acid, and punicalagin) were observed to be ultimately degraded to chebulic acid, gallic acid, and ellagic acid during sunlight-drying of the fresh fruits. As a result, our study indicated that CF and its adulterants could be distinguished by the observed 12 PTCs, which were mainly distributed in the exocarp of the fruits. The HTs were prone to degrade into the three simple phenolcarboxylic acids during drying or processing, allowing us to obtain a more comprehensive understanding of the PTCs, with great significance in the improved quality of CF and related products.

Compound electrolyte intraocular irrigating solution produces better effects on vision recovery of cataract patients after surgery than Ringer lactate solution.

PURPOSE: Intraocular irrigating solution is extensively applied in cataract surgery. This paper explored the difference and relationship between optical coherence tomography (OCT) and optical quality analysis system (OQAS) parameters induced by compound electrolyte intraocular irrigating solution (CEIIS) or Ringer lactate (RL) solution during uncomplicated cataract surgery. METHODS: Totally 200 senior cataract patients were randomly divided into the CEIIS and RL groups (N = 100 patients/group). The anterior chamber was irrigated by CEIIS or RL during phacoemulsification. Patients were subdivided into diabetes mellitus (DM)+ and DM- groups. The central macular thickness (CMT), hyper reflective foci (HF), modulation transfer function cutoff frequency (MTF cutoff), Strehl ratio (SR), objective scatter index (OSI), and OQAS values (OVs) at 100%, 20%, and 9% contrast levels were measured preoperatively and 1 day and 1 week after operation using spectral-domain optical coherence tomography and OQAS II, respectively. Best-corrected visual acuity (BCVA) was assessed using the Snellen scale, followed by statistical analysis of its logarithm of the minimal angle of resolution. RESULTS: There were no significant differences in clinical characteristics between the CEIIS and RL groups. Both groups exhibited notably increased postoperative CMT, MTF cutoff, SR, OV at 100%, 20%, and 9% contrast levels, and reduced OSI, indicating CEIIS and RL improved postoperative visual quality. CEIIS surpassed RL solution in improving postoperative visual quality, decelerating the increase of macular HF numbers and CMT in DM+ patients and postoperative BCVA. There was no difference between CEIIS and RL in long-term vision improvement. CONCLUSION: CEIIS surpasses RL in postoperative visual recovery and retards increases of macular HF numbers and CMT in senior DM+ cataract patients.

Comparison of image quality between a novel mobile CT scanner and current generation stationary CT scanners.

PURPOSE: Point-of-care imaging with mobile CT scanners offers several advantages, provided that the image quality is satisfactory. Our aim was to compare image quality of a novel mobile CT to stationary scanners for patients in a neurosurgical intensive care unit (ICU). METHODS: From November 2020 to April 2021, all patients above 18 years of age examined by a mobile CT scanner at a neurosurgical ICU were included if they also had a stationary head CT examination during the same hospitalization. Quantitative image quality parameters included attenuation and noise in six predefined regions of interest, as well as contrast-to-noise ratio between gray and white matter. Subjective image quality was rated on a 4-garde scale, by four radiologists blinded to scanner parameters. RESULTS: Fifty patients were included in the final study population. Radiation dose and image attenuation values were similar for mobCT and stationary CTs. There was a small statistically significant difference in subjective quality rating between mobCT and stationary CT images. Two radiologists favored the stationary CT images, one was neutral, and one favored mobCT images. For overall image quality, 14% of mobCT images were rated grade 1 (poor image quality) compared to 8% for stationary CT images. CONCLUSION: Point-of-care brain CT imaging was successfully performed on clinical neurosurgical ICU patients with small reduction in image quality, predominantly affecting the posterior fossa, compared to high-end stationary CT scanners.

A novel GIS-based multicriteria analysis approach for ascertaining the catchment-scale degradation of a Himalayan wetland.

Wetland degradation through a diverse spectrum of anthropogenic stressors worldwide has taken a heavy toll on the health of wetlands. This study examined the health of a semi-urban wetland Bodsar, located in the Kashmir Himalaya using multicriteria analysis approach assimilating data on land use land cover (LULC), landscape fragmentation, soil loss, and demography. Wetland and catchment-scale land system changes from 1980 to 2022 were assessed using high-resolution imagery. Fragmentation of the natural landscape was assessed using the Landscape Fragmentation Tool (LFT) and soil loss was assessed using the Revised Universal Soil Loss Equation (RUSLE). In addition, the water quality was examined at 12 sites distributed across the wetland using standard methods. Satellite data revealed 12 categories of land use with areas under exposed rock, orchards, built-up and sparse forest having increased by 1005%, 623%, 274%, and 37% respectively. LFT indicated that the core (>500 acres) and core (<250 acres) zones decreased by approximately 16% and 64%, respectively, whereas the areas under the perforated, edge and patch classes increased significantly. RUSLE estimates show a ∼77% increase in soil erosion from 116.26 Mg a-1 in 1980 to 205.68 Mg a-1 in 2022, mostly due to changes in LULC. Total phosphorus (0.195-2.04 mg L -1), nitrate nitrogen (0.306-2.79 mg L -1), and total dissolved solids (543-774 mg L-1) indicated nutrient enrichment of the wetland influenced by anthropogenically-driven land system changes. The wetland degradation index revealed that 21% of the wetland experienced high-to-severe degradation, 62% experienced moderate degradation, and 17% did not face any significant degradation pressure. The novel GIS-based approach adopted in this study can act as a prototype for ascertaining the catchment-scale degradation of wetlands worldwide.

Intense pulsed-light treatment improves objective optical quality in patients with meibomian gland dysfunction.

BACKGROUND: To evaluate changes in objective optical quality following intense pulsed light (IPL) treatment combined with meibomian gland (MG) expression (MGX) in patients with MG dysfunction (MGD). METHODS: This retrospective cross-sectional study included MGD-related dry eye disease (DED) patients who received IPL treatment between March and December 2021 at Kim's Eye Hospital, Seoul, Republic of Korea. Each patient underwent four sessions of IPL treatment using Lumenis M22 (Lumenis Ltd., Yokneam, Israel) and MGX at three-week intervals. RESULTS: This study included 90 eyes from 45 patients with MGD. The mean age was 52.3 ± 16.1 years (range, 20-75 years), and 53.3% (24/45) of patients were female. Compared with the baseline, all clinical symptoms and signs significantly improved after IPL treatment combined with MGX. All optical quality parameters obtained with an optical quality analysis system (OQAS: Visiometrics, Castelldefels, Spain) have improved significantly over the baseline (p < 0.001). CONCLUSIONS: In patients with MGD, IPL treatment combined with MGX improved the objective optical quality and clinical signs and symptoms of DED.

Detection and Reconstruction of Poor-Quality Channels in High-Density EMG Array Measurements.

High-density electromyography (HD-EMG) arrays allow for the study of muscle activity in both time and space by recording electrical potentials produced by muscle contractions. HD-EMG array measurements are susceptible to noise and artifacts and frequently contain some poor-quality channels. This paper proposes an interpolation-based method for the detection and reconstruction of poor-quality channels in HD-EMG arrays. The proposed detection method identified artificially contaminated channels of HD-EMG for signal-to-noise ratio (SNR) levels 0 dB and lower with ≥99.9% precision and ≥97.6% recall. The interpolation-based detection method had the best overall performance compared with two other rule-based methods that used the root mean square (RMS) and normalized mutual information (NMI) to detect poor-quality channels in HD-EMG data. Unlike other detection methods, the interpolation-based method evaluated channel quality in a localized context in the HD-EMG array. For a single poor-quality channel with an SNR of 0 dB, the F1 scores for the interpolation-based, RMS, and NMI methods were 99.1%, 39.7%, and 75.9%, respectively. The interpolation-based method was also the most effective detection method for identifying poor channels in samples of real HD-EMG data. F1 scores for the detection of poor-quality channels in real data for the interpolation-based, RMS, and NMI methods were 96.4%, 64.5%, and 50.0%, respectively. Following the detection of poor-quality channels, 2D spline interpolation was used to successfully reconstruct these channels. Reconstruction of known target channels had a percent residual difference (PRD) of 15.5 ± 12.1%. The proposed interpolation-based method is an effective approach for the detection and reconstruction of poor-quality channels in HD-EMG.

Industrial Product Quality Analysis Based on Online Machine Learning.

During industrial production activities, industrial products serve as critical resources whose performance is subject to various external factors and usage conditions. To ensure uninterrupted production processes and to guarantee the safety of the production personnel, a real-time analysis of the industrial product quality and subsequent decision making are essential. Conventional detection methods have inherent limitations in meeting the real-time demands of processing large volumes of data and achieving high response speeds. For instance, the regular inspection and maintenance of cars can be time-consuming and labor-intensive if performed manually. Furthermore, monitoring the damage situation of bearings in real time through a manual inspection may lead to delays and may hinder production efficiency. Therefore, this paper presents online machine-learning-based methods to address these two practical problems and simulates them on various datasets to meet the requirements of efficiency and speed. Prior to being fed into the network for training, the data undergo identity parsing to transform them into easily identifiable streaming data. The training process demonstrates that online machine learning ensures timely model updates as small batches of data are sent to the network. The test results indicate that the online learning method exhibits highly stable and effective performance, optimizing the training process.

Study of the effectiveness of wavelet genetic programming model for water quality analysis in the Uttar Pradesh region.

Water constitutes an essential part of the earth as it helps in making the environment greener and support life. But water quality and availability are drastically affected by rising water pollution and its poor sanitation. Water gets contaminated due to the excessive use of chemicals by the industries, fertilizers, and pesticides by the farmers. Not only the surface water, groundwater and river water are also getting contaminated. Several published work in Indian context have used different models for the prediction of water quality. Some of them performed poorly due to the presence of irrelevant and missing data in the training samples. Moreover, these studies have assessed water quality on the basis of biochemical oxygen demand (BOD) and coliform and chemical oxygen demand (COD), whereas dissolved oxygen(DO) is one of the most important parameters in terms of water quality assessment as it is considered a key determinant of pollution. Thus, there is a strong need to categorically identify and visualize the DO as one of the key components responsible for deteriorating the quality of water in Indian context. The main objective of this work is to build a wavelet genetic programming (WGP)-based workflow model for the assessment of water quality in 13 rivers of Uttar Pradesh region. WGP model has a unique feature of discarding the redundant and irrelevant data values from the source data. The proposed WGP model has given promising results which can be attributed to two factors: firstly, the novel use of Morlet wavelet in place of the widely popular Db wavelet, as the mother wavelet, and secondly, the use of MICE technique for missing value imputation in the pre-processing stage. The proposed model not only cleans the data but also demonstrates the feasibility of using DO values as one of the prime factors to assess the water quality.

Spatio-temporal investigation of physico-chemical water quality parameters based on comparative assessment of QUAL 2Kw and WASP model for the upper reaches of Yamuna River stretching from Paonta Sahib, Sirmaur district to Cullackpur, North Delhi districts of North India.

An accurate investigation of bio-physical and chemical parameters as proxy of in situ water quality conditions in the Himalayan region is highly challenging owing to cumbersome, strenuous, and physically exhausting sampling exercises at high altitude locations. The upper stretches of Yamuna River in the Himachal Pradesh are typical examples of such sampling locations that have rarely been examined in the past studies. A widely accepted and recognized QUAL 2Kw model is applied for estimating the water quality parameters on the upper segment of the Yamuna River from Paonta Sahib to Cullackpur. These water quality indicators mainly included electric conductivity, pH, dissolved oxygen, temperature, carbonaceous biological oxygen demand (CBOD), inorganic suspended solids, total nitrogen, total phosphorus, and alkalinity, which were systematically investigated for predicting the spatio-temporal trends during the year 2018. A total of 12 distantly located river sites were identified for sample collection and data validation using QUAL 2Kw model. The present investigation attempts to reveal long-term degraded impact of untreated wastewater and biased agricultural practices on the water quality conditions over the upper stretches of Yamuna River. The QUAL 2Kw-derived values for selected variables were inter-compared with in situ values, and any deviation from measured values was ascertained based on meaningful statistical measures. The lower error of RMSE, MRE, and BIAS, corresponding to < 15%, ± 10%., ± 20%, and ~ 1 slope evidently indicated better matchup of values, wherein, higher slope correlation coefficient (R2) of ~ 90% indicated the robust performance of the QUAL 2Kw algorithm in accurately predicting the chosen variables. A comparative assessment of QUAL 2Kw and WASP has been performed to justify aptness of water quality model in scenarios of lean flow.

[Content analysis and quality evaluation of main active components and mineral elements of Cynomorium songaricum in different habitats].

To clarify the content characteristics of the main active components and mineral elements of Cynomorium songaricum under different habitat conditions, and further explore the relationship between the quality of C. songaricum and habitats, this study took C. songaricum from 25 different habitats in China as the research object, and measured the contents of 8 main active components and 12 mineral elements separately. Diversity analysis, correlation analysis, principal component analysis and cluster analysis were carried out. The results showed that the genetic diversity of total flavonoids, ursolic acid, ether extract, potassium(K), phosphorus(P) and zinc(Zn) in C. songaricum was high. The coefficient of variation of crude polysaccharide, ether extract, gallic acid, protocatechuic aldehyde, catechin, epicatechin, calcium(Ca), sodium(Na), magnesium(Mg), sulfur(S), iron(Fe), manganese(Mn), selenium(Se) and nickel(Ni) were all over 36%, indicating that the quality of C. songaricum was significantly affected by habitats. There were strong synergistic and weak antagonistic effects among the contents of the 8 active components, and complex antagonistic and synergistic effects among the contents of the 12 mineral elements. Principal component analysis revealed that crude polysaccharide, ursolic acid, catechin, epicatechin and total flavonoids could be used as the characteristic components to evaluate the quality of C. songaricum, and Na, copper(Cu), Mn and Ni were the characteristic elements to evaluate the quality of C. songaricum. In cluster ana-lysis, the second group with the main active components as cluster center had better quality in terms of the content of active substances, and the second group with the mineral elements as cluster center had higher utilization potential in the exploitation of mineral elements. This study could provide a basis for resource evaluation and breeding of excellent varieties of C. songaricum in different habitats, and provide a reference for cultivation and identification of C. songaricum.

[Chemical composition analysis and value evaluation of stems and leaves of Astragalus membranaceus var. mongholicus].

This study aimed to provide data support for resource utilization of the stems and leaves of Astragalus membranaceus var. mongholicus(SLAM) by analyzing and evaluating the chemical constituents. The crude protein, crude fiber, and soluble saccharide of SLAM were analyzed by Kjeldahl method, filtration method, and UV-Vis spectrophotometry, respectively. The nucleosides, amino acids, flavonoids, and saponins of SLAM were analyzed by ultraperformance liquid chromatography-triple quadrupole mass spectrometry(UPLC-TQ-MS). Combined with principal component analysis(PCA), the quality difference of resource components of SLAM was comprehensively evaluated. The results showed that the average content of crude protein, crude fiber, total polysaccharide, and redu-cing sugar in SLAM was 5.11%, 30.33%, 11.03 mg·g~(-1), and 31.90 mg·g~(-1), respectively. Six nucleosides, 15 amino acids, 22 flavonoids, and one saponin were detected, with an average content of 1.49 mg·g~(-1), 6.00 mg·g~(-1), 1.86 mg·g~(-1), and 35.67 µg·g~(-1), respectively. The content of various types of chemical components in SLAM differed greatly in different harvesting periods and growing years. The results of PCA showed that the quality of SLAM produced in Ningxia was superior. The results can provide references for the utilization of SLAM.

Significance of Mg-hardness and fluoride in drinking water on chronic kidney disease of unknown etiology in Monaragala, Sri Lanka.

The epidemic of chronic kidney disease of unknown etiology (CKDu) that contributes significantly to morbidity and mortality rates among dry-zonal farming communities has become a public health priority in Sri Lanka. Though a large number of hypotheses were introduced as causative factors, none of them have been confirmed so far. As drinking water quality is among the most suspected causative factors for the emergence of CKDu, a detailed hydro-geochemical investigation was carried out concurrently with the population screening in the Monaragala district of Sri Lanka where high incidences of CKDu are reported. A population screening was performed selecting 46,754 people using both dipstick proteinuria test and Albumin-Creatinine Ratio (ACR). The results revealed that the disease prevalence is about 6.7 % in the district. A total of 60 groundwater samples, 30 each, were collected from CKDu-prevalent locations and control locations where there are no CKDu cases reported. The samples were analyzed to identify any possible linkage between water quality and disease prevalence. Concentrations of hardness, F-, Na+, and Mg2+ in groundwater revealed a statistically significant difference between CKDu and control wells at a confident level of p = 0.05. The study revealed that alkali (Na++K+) and alkaline earth cations (Mg2+, Ca2+, Sr2+, Ba2+) were relatively higher in drinking water sources used by CKDu patients, compared to the well waters used by healthy individuals. Nearly 87 % of the wells used by CKDu cases showed higher fluoride levels that exceed the threshold level (1.0 mg L-1). Contents of nephrotoxic trace elements such as As, Cd, and Pb were found to be comparable in both types of wells and were well below the WHO permissible levels, thus negating their prime influence on the CKDu prevalence. It is obtrusive that the elevated fluoride levels together with water hardness associated with higher Mg2+ levels have a possible relation with CKDu and may influence the disease progression.