Low-Cycle Fatigue Behavior and the Combined Cyclic Hardening Material Model of Plate-Shaped Zn-22Al Alloy for Seismic Dampers.

This study investigates the potential of the plate-shaped Zn-22 wt.% Al (Zn-22Al) alloy as an innovative energy dissipation material for seismic damping devices, since plate-shaped material is more suitable to fabricate large-scale devices for building structures. The research begins with the synthesis of Zn-22Al alloy, given its unavailability in the commercial market. Monotonic tensile tests and low-cycle fatigue tests are performed to analyze material properties and fatigue performance of plate-shaped specimens. Monotonic tensile curves and cyclic stress-strain curves, along with SEM micrographs for microstructure and fracture surface analysis, are acquired. The combined cyclic hardening material model is calibrated to facilitate finite element analysis. Experimental results reveal exceptional ductility in Zn-22Al alloy, achieving a fracture strain of 200.37% (1.11 fracture strain). Fatigue life ranges from 1126 to 189 cycles with increasing strain amplitude (±0.8% to ±2.5%), surpassing mild steel by at least 6 times. The cyclic strain-life relationships align well with the Basquin-Coffin-Manson relationship. The combined kinematic/isotropic hardening model in ABAQUS accurately predicts the hysteretic behavior of the material, showcasing the promising potential of Zn-22Al alloy for seismic damping applications.

Fiber Synergy of Polyvinyl Alcohol and Steel Fibers on the Bond Behavior of a Hybrid Fiber-Reinforced Cementitious Composite.

Based on multi-scale characteristics inherent in the cracking process of cementitious composites, fibers with different geometric dimensions are simultaneously used to restrain the formation and development of cracks at different scales. Accordingly, hybrid fiber-reinforced cementitious composites (HyFRCCs) exhibit excellent bond behavior and deformation capacity in terms of tension and compression, accompanied by higher damage tolerance. Using these benefits of the mechanical properties of HyFRCCs, the structural performance of HyFRCC structures under complex loading conditions can be improved. To objectively evaluate the contributions of all fibers to the mechanical properties of HyFRCCs, steel macro-fibers, and polyvinyl alcohol (PVA) micro-fibers were used to design several reinforced cementitious composites. Four of the specimens were mono-fibrous cementitious composites, three specimens were cementitious composites reinforced with hybrid fibers, and one was a non-fibrous cementitious composite. The synergy effect of the steel and PVA fibers was analyzed using various fiber combinations. The results indicated a significant enhancement of the bonding properties of HyFRCCs through the incorporation of PVA and steel fibers. Specifically, the peak bond strength, peak slip displacement, and residual bond strength exhibited increments ranging from 31.0% to 41.7%, 60.6% to 118.4%, and 34.6% to 391.3%, respectively, in comparison to the reference test block. Notably, the combined presence of the PVA and steel fibers consistently demonstrated a positive confounding effect on the residual bond strength. However, negative confounding effects were observed in terms of the peak bond strength and peak slip displacement, particularly with 1.0% steel fiber content and 0.5% PVA fiber content.

Developing and validating a clinlabomics-based machine-learning model for early detection of retinal detachment in patients with high myopia.

BACKGROUND: Retinal detachment (RD) is a vision-threatening disorder of significant severity. Individuals with high myopia (HM) face a 2 to 6 times higher risk of developing RD compared to non-myopes. The timely identification of high myopia-related retinal detachment (HMRD) is crucial for effective treatment and prevention of additional vision impairment. Consequently, our objective was to streamline and validate a machine-learning model based on clinical laboratory omics (clinlabomics) for the early detection of RD in HM patients. METHODS: We extracted clinlabomics data from the electronic health records for 24,440 HM and 5607 HMRD between 2015 and 2022. Lasso regression analysis assessed fifty-nine variables, excluding collinear variables (variance inflation factor > 10). Four models based on random forest, gradient boosting machine (GBM), generalized linear model, and Deep Learning Model were trained for HMRD diagnosis and employed for internal validation. An external test of the models was done. Three random data sets were further processed to validate the performance of the diagnostic model. The primary outcomes were the area under the receiver operating characteristic curve (AUC) and the area under the precision-recall curve (AUCPR) to diagnose HMRD. RESULTS: Nine variables were selected by all models. Given the AUC and AUCPR values across the different sets, the GBM model was chosen as the final diagnostic model. The GBM model had an AUC of 0.8550 (95%CI = 0.8322-0.8967) and an AUCPR of 0.5584 (95%CI = 0.5250-0.5879) in the training set. The AUC and AUCPR in the internal validation were 0.8405 (95%CI = 0.8060-0.8966) and 0.5355 (95%CI = 0.4988-0.5732). During the external test evaluation, it reached an AUC of 0.7579 (95%CI = 0.7340-0.7840) and an AUCPR of 0.5587 (95%CI = 0.5345-0.5880). A similar discriminative capacity was observed in the three random data sets. The GBM model was well-calibrated across all the sets. The GBM-RD model was implemented into a web application that provides risk prediction for HM individuals. CONCLUSION: GBM algorithms based on nine features successfully predicted the diagnosis of RD in patients with HM, which will help ophthalmologists to establish a preliminary diagnosis and to improve diagnostic accuracy in the clinic.

Response of antioxidant activity, active constituent and rhizosphere microorganisms of Salvia miltiorrhiza to combined application of microbial inoculant, microalgae and biochar under Cu stress.

Salvia miltiorrhiza, a widely used medicinal herb renowned for its properties in promoting blood circulation, removing blood stasis and alleviating pain, is currently facing quality degradation due to excessive heavy metal levels, posing a threat to medication safety. In order to investigate the effects of microbial inoculant, microalgae and biochar on the growth of Salvia miltiorrhiza under copper (Cu) stress, as well as its Cu absorption, antioxidant activity, active component contents and rhizosphere microbial community, a pot experiment was conducted. Salvia miltiorrhiza plants were cultivated in the soil containing 400 mg/kg of Cu for six months and treated with microbial inoculant, microalgae and biochar, either individually or in combination. Almost all soil amendment treatments led to an increase in root biomass. Notably, co-application of microbial inoculant and microalgae had the optimal effect with a 63.07 % increase compared to the group treated solely with Cu. Moreover, when microbial inoculant was applied alone or in combination with microalgae, the Cu content in plant roots was reduced by 19.29 % and 25.37 %, respectively, whereas other treatments failed to show a decreasing trend. Intriguingly, Cu stress increased the active component contents in plant roots, and they could also be enhanced beyond non-stress levels when microbial inoculant and microalgae were applied together or in combination with biochar. Analyses of plant antioxidant activity, soil properties and rhizosphere microorganisms indicated that these amendments may alleviate Cu stress by enhancing peroxidase activity, facilitating plant nutrient absorption, and enriching beneficial microorganisms capable of promoting plant growth and mitigating heavy metal-induced damage. This study suggests that the combined application of microbial inoculant and microalgae can reduce Cu levels in Salvia miltiorrhiza while enhancing its quality under Cu stress.

Identification of toxic Gelsemium elegans in processed food and honey based on real-time PCR analysis.

Gelsemium elegans (GE) is a widely distributed hypertoxic plant that has caused many food poisoning incidents. Its pollen can also be collected by bees to produce toxic honey, posing a great threat to the health and safety of consumers. However, for the complex matrices such as cooked food and honey, it is challenging to perform composition analysis. It is necessary to establish more effective strategies for investigating GE contamination. In this study, the real-time PCR (qPCR) analysis combined with DNA barcode matK was proposed for the identification and detection of GE. Fifteen honey samples along with twenty-eight individuals of GE and the common confusable objects Lonicera japonica, Ficus hirta, Stellera chamaejasme and Chelidonium majus were gathered. Additionally, the food mixtures treated with 20-min boiling and 30-min digestion were prepared. Specific primers were designed, and the detection capability and sensitivity of qPCR in honey and boiled and digested food matrices were tested. The results demonstrated that the matK sequence with sufficient mutation sites was an effective molecular marker for species differentiation. GE and the confusable species could be clearly classified by the fluorescence signal of qPCR assay with a high sensitivity of 0.001 ng/µl. In addition, this method was successfully employed for the detection of deeply processed food materials and honey containing GE plants which even accounted for only 0.1 %. The sequencing-free qPCR approach undoubtedly can serve as a robust support for the quality supervision of honey industry and the prevention and diagnosis of food poisoning.

DNA metabarcoding analysis of fungal community on surface of four root herbs.

Objective: Angelicae Sinensis Radix (ASR, Danggui in Chinese), Cistanches Herba (CH, Roucongrong in Chinese), Ginseng Radix et Rhizoma (PG, Renshen in Chinese), and Panacis Quinquefolii Radix (PQ, Xiyangshen in Chinese), widely used as medicine and dietary supplement around the world, are susceptible to fungal and mycotoxin contamination. In this study, we aim to analyze their fungal community by DNA metabarcoding. Methods: A total of 12 root samples were collected from three main production areas in China. The samples were divided into four groups based on herb species, including ASR, CH, PG, and PQ groups. The fungal community on the surface of four root groups was investigated through DNA metabarcoding via targeting the internal transcribed spacer 2 region (ITS2). Results: All the 12 samples were detected with fungal contamination. Rhizopus (13.04%-74.03%), Aspergillus (1.76%-23.92%), and Fusarium (0.26%-15.27%) were the predominant genera. Ten important fungi were identified at the species level, including two potential toxigenic fungi (Penicillium citrinum and P. oxalicum) and eight human pathogenic fungi (Alternaria infectoria, Candida sake, Hyphopichia burtonii, Malassezia globosa, M. restricta, Rhizopus arrhizus, Rhodotorula mucilaginosa, and Ochroconis tshawytschae). Fungal community in ASR and CH groups was significantly different from other groups, while fungal community in PG and PQ groups was relatively similar. Conclusion: DNA metabarcoding revealed the fungal community in four important root herbs. This study provided an important reference for preventing root herbs against fungal and mycotoxin contamination.

Research progress on remediation of organochlorine pesticide contamination in soil.

Deteriorated soil pollution has grown into a worldwide environmental concern over the years. Organochlorine pesticide (OCP) residues, featured with ubiquity, persistence and refractoriness, are one of the main pollution sources, causing soil degradation, fertility decline and nutritional imbalance, and severely impacting soil ecology. Furthermore, residual OCPs in soil may enter the human body along with food chain accumulation and pose a serious health threat. To date, many remediation technologies including physicochemical and biological ways for organochlorine pollution have been developed at home and abroad, but none of them is a panacea suitable for all occasions. Rational selection and scientific decision-making are grounded in in-depth knowledge of various restoration techniques. However, soil pollution treatment often encounters the interference of multiple factors (climate, soil properties, cost, restoration efficiency, etc.) in complex environments, and there is still a lack of systematic summary and comparative analysis of different soil OCP removal methods. Thus, to better guide the remediation of contaminated soil, this review summarized the most commonly used strategies for OCP removal, evaluated their merits and limitations and discussed the application scenarios of different methods. It will facilitate the development of efficient, inexpensive and environmentally friendly soil remediation strategies for sustainable agricultural and ecological development.

DNA Metabarcoding Reveals the Fungal Community on the Surface of Lonicerae Japonicae Flos, an Edible and Medicinal Herb.

Lonicerae Japonicae Flos (LJF) has been globally applied as an herbal medicine and tea. A number of reports recently revealed fungal and mycotoxin contamination in medicinal herbs. It is essential to analyze the fungal community in LJF to provide an early warning for supervision. In this study, the fungal community in LJF samples was identified through DNA metabarcoding. A total of 18 LJF samples were collected and divided based on the collection areas and processing methods. The results indicated that Ascomycota was the dominant phylum. At the genus level, Rhizopus was the most abundant, followed by Erysiphe and Fusarium. Ten pathogenic fungi were detected among the 41 identified species. Moreover, Rhizopus, Fusarium, and Aspergillus had lower relative abundances in LJF samples under oven drying than under other processing methods. This work is expected to provide comprehensive knowledge of the fungal community in LJF and a theoretical reference for enhanced processing methods in practical manufacturing.

Development of nucleotide signatures for common poisonous organisms provides a new strategy for food poisoning diagnosis.

DNA barcoding is widely used in toxic species authentication, but due to serious DNA degradation of forensic materials, the application of full-length barcode sequences in food poisoning diagnosis is greatly limited. Nucleotide signature, a shorter specific molecular marker, derived from traditional DNA barcoding has been proposed as an emerging tool of toxic species detection in deeply processed materials. In this study, to resolve the frequent food poisoning accidents with unknown origin, we envisioned developing a nucleotide signature data set of common poisonous organisms and combining high-throughput sequencing (HTS) to reveal the poisoning cause. Ninety-three individuals and 1093 DNA barcode sequences of twelve common poisonous plants, fish, mushrooms and their related species were collected. Through sequence alignment and screening, the nucleotide signatures were respectively developed and validated as their specific molecular markers. The sequence length varied from 19 bp to 38 bp. These fragments were conserved within the same species or genera, and the specificity between related species has been also demonstrated. To further evaluate the application potential of nucleotide signature in forensic diagnosis, simulated forensic specimens (SFS) containing different poisonous ingredients were sequenced by HTS with PCR-free libraries. As a result, the nucleotide signature was successfully captured from original HTS data without assembly and annotation, accompanied by a high detection sensitivity of 0.1 ng/µl in mixture system. Therefore, this method was suitable for the assay of forensic materials with serious DNA degradation. The present study undoubtedly provides a new perspective and strong support for the detection of toxic ingredients and the diagnosis of food poisoning.

Development and validation of a routine blood parameters-based model for screening the occurrence of retinal detachment in high myopia in the context of PPPM.

Background/aims: Timely detection and treatment of retinal detachment (RD) could effectively save vision and reduce the risk of progressing visual field defects. High myopia (HM) is known to be associated with an increased risk of RD. Evidently, it should be clearly discriminated the individuals with high or low risk of RD in patients with HM. By using multi-parametric analysis, risk assessment, and other techniques, it is crucial to create cutting-edge screening programs that may be utilized to improve population eye health and develop person-specific, cost-effective preventative, and targeted therapeutic measures. Therefore, we propose a novel, routine blood parameters-based prediction model as a screening program to help distinguish who should offer detailed ophthalmic examinations for RD diagnosis, prevent visual field defect progression, and provide personalized, serial monitoring in the context of predictive, preventive, and personalized medicine (PPPM/3 PM). Methods: This population-based study included 20,870 subjects (HM = 19,284, HMRD = 1586) who underwent detailed routine blood tests and ophthalmic evaluations. HMRD cases and HM controls were matched using a nested case-control design. Then, the HMRD cases and HM controls were randomly assigned to the discovery cohort, validation cohort 1, and validation cohort 2 maintaining a 6:2:2 ratio, and other subjects were assigned to the HM validation cohort. Receiver operating characteristic curve analysis was performed to select feature indexes. Feature indexes were integrated into seven algorithm models, and an optimal model was selected based on the highest area under the curve (AUC) and accuracy. Results: Six feature indexes were selected: lymphocyte, basophil, mean platelet volume, platelet distribution width, neutrophil-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio. Among the algorithm models, the algorithm of conditional probability (ACP) showed the best performance achieving an AUC of 0.79, a diagnostic accuracy of 0.72, a sensitivity of 0.71, and a specificity of 0.74 in the discovery cohort. A good performance of the ACP model was also observed in the validation cohort 1 (AUC = 0.81, accuracy = 0.72, sensitivity = 0.71, specificity = 0.73) and validation cohort 2 (AUC = 0.77, accuracy = 0.71, sensitivity = 0.70, specificity = 0.72). In addition, ACP model calibration was found to be good across three cohorts. In the HM validation cohort, the ACP model achieved a diagnostic accuracy of 0.81 for negative classification. Conclusion: We have developed a routine blood parameters-based model with an ACP algorithm that could potentially be applied in the clinic with a PPPM approach for serial monitoring and predicting the occurrence of RD in HM and can facilitate the prevention of HM progression to RD. According to the current study, routine blood measures are essential in patient risk classification, predictive diagnosis, and targeted therapy. Therefore, for high-risk RD persons, novel screening programs and prompt treatment plans are essential to enhance individual outcomes and healthcare offered to the community with HM. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00319-3.

DNA barcoding in herbal medicine: Retrospective and prospective.

DNA barcoding has been widely used for herb identification in recent decades, enabling safety and innovation in the field of herbal medicine. In this article, we summarize recent progress in DNA barcoding for herbal medicine to provide ideas for the further development and application of this technology. Most importantly, the standard DNA barcode has been extended in two ways. First, while conventional DNA barcodes have been widely promoted for their versatility in the identification of fresh or well-preserved samples, super-barcodes based on plastid genomes have rapidly developed and have shown advantages in species identification at low taxonomic levels. Second, mini-barcodes are attractive because they perform better in cases of degraded DNA from herbal materials. In addition, some molecular techniques, such as high-throughput sequencing and isothermal amplification, are combined with DNA barcodes for species identification, which has expanded the applications of herb identification based on DNA barcoding and brought about the post-DNA-barcoding era. Furthermore, standard and high-species coverage DNA barcode reference libraries have been constructed to provide reference sequences for species identification, which increases the accuracy and credibility of species discrimination based on DNA barcodes. In summary, DNA barcoding should play a key role in the quality control of traditional herbal medicine and in the international herb trade.

Bacillus and microalgae biofertilizers improved quality and biomass of Salvia miltiorrhiza by altering microbial communities.

Objective: Biofertilizers are reliable alternatives to chemical fertilizers due to various advantages. However, the effect of biofertilizers on Salvia miltiorrhiza yield and quality and the possible mechanisms remain little known. Here, an experiment was conducted in S. miltiorrhiza field treated with two kinds of biofertilizers including Bacillus and microalgae. Methods: A field experiment was conducted on S. miltiorrhiza of one year old. The biofertilizers were applied at six treatments: (i) control check, CK; (ii) microalgae, VZ; (iii) Bacillus, TTB; (iv) microalgae + Bacillus (1:1), VTA; (v) microalgae + Bacillus (0.5:1), VTB; (vi) microalgae + Bacillus (1:0.5), VTC. Here, high-throughput sequencing, ICP-MS and UPLC were employed to systematically characterize changes of microbial diversity and structure composition, heavy metals content and bioactive compounds, respectively. Results: Compared to CK, root biomass increased by 29.31%-60.39% (P < 0.001). Meanwhile, bioactive compounds were higher than CK after the application of the biofertilizers, peculiarly in TTB and VTB. However, the content of Pb contents in roots significantly reduced by 46.03% and 37.58% respectively in VTC and TTB (P < 0.05). VTA application notably increased the available nitrogen content by 53.03% (P < 0.05), indicating the improvement of soil fertility. Significantly, bacterial and fungal Chao I diversity indices showed an increasing trend with biofertilizer application (P < 0.05), and biofertilizer amendment enriched the rhizosphere soil with beneficial microorganisms that have abilities on promoting plant growth (Achromobacter and Penicillium), adsorbing heavy metal (Achromobacter and Beauveria), controlling plant pathogen (Plectosphaerella, Lechevalieria, Sorangium, Phlebiopsis and Beauveria) and promoting the accumulation of metabolites (Beauveria and Phoma). Conclusion: Bacillus and microalgae biofertilizers improved the quality and biomass of S. miltiorrhiza by altering microbial communities in soil.

Contributions of Beneficial Microorganisms in Soil Remediation and Quality Improvement of Medicinal Plants.

Medicinal plants (MPs) are important resources widely used in the treatment and prevention of diseases and have attracted much attention owing to their significant antiviral, anti-inflammatory, antioxidant and other activities. However, soil degradation, caused by continuous cropping, excessive chemical fertilizers and pesticide residues and heavy metal contamination, seriously restricts the growth and quality formation of MPs. Microorganisms, as the major biota in soil, play a critical role in the restoration of the land ecosystem. Rhizosphere microecology directly or indirectly affects the growth and development, metabolic regulation and active ingredient accumulation of MPs. Microbial resources, with the advantages of economic efficiency, harmless to environment and non-toxic to organisms, have been recommended as a promising alternative to conventional fertilizers and pesticides. The introduction of beneficial microbes promotes the adaptability of MPs to adversity stress by enhancing soil fertility, inhibiting pathogens and inducing systemic resistance. On the other hand, it can improve the medicinal quality by removing soil pollutants, reducing the absorption and accumulation of harmful substances and regulating the synthesis of secondary metabolites. The ecological and economic benefits of the soil microbiome in agricultural practices are increasingly recognized, but the current understanding of the interaction between soil conditions, root exudates and microbial communities and the mechanism of rhizosphere microecology affecting the secondary metabolism of MPs is still quite limited. More research is needed to investigate the effects of the microbiome on the growth and quality of different medicinal species. Therefore, the present review summarizes the main soil issues in medicinal plant cultivation, the functions of microbes in soil remediation and plant growth promotion and the potential mechanism to further guide the use of microbial resources to promote the ecological cultivation and sustainable development of MPs.

Detection of Highly Poisonous Nerium oleander Using Quantitative Real-Time PCR with Specific Primers.

Nerium oleander is one of the most poisonous plants, and its accidental ingestion has frequently occurred in humans and livestock. It is vital to develop a rapid and accurate identification method for the timely rescue of oleander-poisoned patients and the investigation of poisoning cases. In this study, a specific and highly sensitive quantitative real-time PCR (qPCR)-based method was developed to identify oleander in mixture systems and simulated forensic specimens (SFS). First, a new pair of oleander-specific primers, JZT-BF/BR, was designed and validated. Then, a qPCR method was developed using the primers, and its detective sensitivity was examined. The results showed that JZT-BF/BR could specifically identify oleander in forage and food mixtures, and qPCR was capable of accurate authentication even at a low DNA concentration of 0.001 ng/µL. This method was further applied to the analysis of SFS containing different ratios of N. oleander. The method was confirmed to be applicable to digested samples, and the detection limit reached 0.1% (w/w) oleander in mixture systems. Thus, this study undoubtedly provides strong support for the detection of highly toxic oleander and the diagnosis of food poisoning in humans and animals.

Microbial inoculants and garbage fermentation liquid reduced root-knot nematode disease and As uptake in Panax quinquefolium cultivation by modulating rhizosphere microbiota community.

Objective: To find a suitable ecological cultivation measure to solve the problem of root-knot nematode disease of Panax quinquefolium (Panacis Quinquefolii Radix) and the heavy metals accumulating in its roots. Methods: Three-year-old P. quinquefolium was treated with four different combinations of microbial inoculant (MI) and garbage fermentation liquid (GFL) [the joint application of 'TuXiu' MI and Fifty potassium MI (TF), the combination use of 'No. 1' MI and Fifty potassium MI (NF), 'Gulefeng' poly-γ-glutamic acid MI (PGA), GFL], and the untreated control (CK). Here, high-throughput sequencing, ICP-MS and UPLC were employed to systematically characterize changes of microbial diversity and structure composition, heavy metals (As, Cd and Pb) content and ginsenoside content among different treatments. Results: The results revealed that different MIs and GFL could increase the root dry weight of P. quinquefolium, PGA enhanced it by 83.24%, followed by GFL (49.93%), meanwhile, PGA and GFL were able to lessen root-knot nematode disease incidence by 57.25% and 64.35%. The treatment of PGA and GFL can also effectively reduce heavy metals in roots. The As content in GFL and PGA was decreased by 52.17% and 43.48% respectively, while the Cd and Pb contents of GFL and PGA was decreased somewhat. Additionally, the content of total ginsenosides was increased by 42.14% and 42.07%, in response to TF and NF, respectively. Our metagenomic analysis showed that the relative abundance of particular soil microbial community members related to the biocontrol of root-knot nematode disease and plant pathogen (i.e., Chaetomium in NF, Xylari in GFL, and Microascus in PGA), heavy metal bioremediation (Hyphomacrobium in PGA and Xylaria in GFL), and nitrogen fixation (Nordella and Nitrospira in TF) was significantly increased; notably, potential harmful microflora, such as Plectosaphaerella and Rhizobacter, were more abundant in the control group. Conclusion: MI and GFL could improve the quality of P. quinquefolium by modifying its rhizosphere microbial community structure and composition, both of them are beneficial to the development of ecological cultivation of P. quinquefolium.

Development of a Genus-Universal Nucleotide Signature for the Identification and Supervision of Ephedra-Containing Products.

Ephedra plants generally contain ephedrine alkaloids, which are the critical precursor compounds of methamphetamine (METH). METH could cause serious physical and mental damage, and therefore Ephedra materials are strictly in supervision internationally. However, unlawful utilization of Ephedra herbs and its products still exist. Thus, it is imperative to establish a universal method for monitoring Ephedra ingredients in complex mixtures and processed products. In this study, 224 ITS2 sequences representing 59 taxa within Ephedra were collected, and a 23-bp genus-level nucleotide signature (GTCCGGTCCGCCTCGGCGGTGCG) was developed for the identification of the whole genus. The specific primers MH-1F/1R were designed, and 125 individuals of twelve Ephedra species/varieties were gathered for applicability verification of the nucleotide signature. Additionally, seven batches of Chinese patent medicines containing Ephedra herbs were used to test the application of the nucleotide signature in complex and highly processed materials. The results demonstrated that the 23-bp molecular marker was unique to Ephedra and conserved within the genus. It can be successfully utilized for the detection of Ephedra components in complex preparations and processed products with severe DNA degradation. The method developed in this study could undoubtedly serve as a strong support for the supervision of illegal circulation of Ephedra-containing products.

Detection of Adulteration and Pesticide Residues in Chinese Patent Medicine Qipi Pill Using KASP Technology and GC-MS/MS.

Chinese patent medicines (CPMs) are of great value for the prevention and treatment of diseases. However, adulterants and pesticide residues in CPMs have become the "bottleneck" impeding the globalization of traditional Chinese medicine. In this study, 12 batches of commercially available Qipi pill (a famous CPM recorded in Chinese Pharmacopeia) from different manufacturers were investigated to evaluate their authenticity and quality safety. Considering the severely degraded DNA in CPMs, kompetitive allele specific PCR (KASP) technology combined with DNA mini-barcodes was proposed for the quality regulation of a large number of products in CPM market. The residues of four kinds of pesticides including pentachloronitrobenzene (PCNB), hexachlorocyclohexane (HCH), aldrin, and dichlorodiphenyltrichloroethane (DDT) were quantified using gas chromatography and tandem mass spectrometry (GC-MS/MS). The results indicated that in two of the 12 batches of Qipi pill, the main herbal ingredient Panax ginseng was completely substituted by P. quinquefolius, and one sample was partially adulterated with P. quinquefolius. The PCNB residue was detected in 11 batches of Qipi pill, ranging from 0.11 to 0.46 mg/kg, and the prohibited pesticide HCH was present in four samples. Both adulteration and banned pesticides were found in two CPMs. This study suggests that KASP technology combined with DNA mini-barcodes can be used for the quality supervision of large sample size CPMs with higher efficiency but lower cost. Our findings also provide the insight that pesticide residues in CPMs should be paid more attention in the future.

Identification and poisoning diagnosis of Aconitum materials using a genus-specific nucleotide signature.

Aconitum genus generally contains hypertoxic alkaloids. Poisoning incidents due to the improper ingestion of Aconitum materials frequently occur around the world. DNA barcoding is considered as a powerful tool for species identification, but complete sequences of conventional DNA barcodes are sometimes unattainable from food and highly processed products due to severe DNA degradation. Therefore, a shorter molecular marker will be more profitable for the authentication and poisoning diagnosis of Aconitum materials. In this study, 1246 psbA-trnH sequences and chloroplast genomes representing 183 taxa of Aconitum were collected, and a 23-bp nucleotide signature unique to Aconitum genus (5'-TATATGAGTCATTGAAGTTGCAG-3') was developed. The nucleotide signature was conserved and universal within Aconitum while divergent among other genera. The specific molecular signature was then successfully applied to the detection of processed Aconitum ingredients. To further evaluate the application potential of nucleotide signature in completely unknown mixture samples, boiled food mixtures, containing different ratios of Aconitum materials, were sequenced by high-throughput sequencing technology. The results showed that the nucleotide signature sequence could be directly extracted from raw sequencing data, even at a low DNA concentration of 0.2 ng/µl. Consequently, the 23-bp genus-specific nucleotide signature represents a significant step forward in the use of DNA barcoding to identify processed samples and food mixtures with degraded DNA. This study undoubtedly provides a new perspective and strong support for the identification and detection of Aconitum-containing products, which can be further introduced to the diagnosis of food poisoning.

The complete chloroplast genome of Asarum pulchellum Hemsl. (Aristolochiaceae: Asarum L.).

Asarum pulchellum Hemsley 1890, belonging to Aristolochiaceae family, is a kind of folk herb resource with certain toxicity. In this study, we acquired the complete chloroplast genome of A. pulchellum for its accurate species identification and phylogenetic analysis. The genome is 177,905 bp in size with a typical circular quadripartite structure, consisting of a large single-copy region, a small single-copy region and a pair of inverted repeats. In total, 136 genes were annotated, including 92 protein-coding genes, 36 tRNA genes and eight rRNA genes. In the phylogenetic analysis, A. pulchellum and A. sieboldii formed a sister clade. The chloroplast genome helps further studies of taxonomy and genetic evolution of Aristolochiaceae family.

Association between Red Blood Cell Distribution Width and Diabetic Retinopathy: A 5-Year Retrospective Case-Control Study.

PURPOSE: Red blood cell distribution width (RDW) has been regarded as an emerging biomarker of the general population and cardiovascular disease. In this study, we aimed to evaluate the association between RDW and diabetic retinopathy (DR). METHODS: This case-control study included 167 patients with DR, 131 patients with diabetes mellitus (DM), and 170 age- and sex-matched healthy controls from April 2014 to May 2019. Demographic data, laboratory parameters, and ocular examinations were collected. RESULTS: RDW values of the DR group were significantly higher than those of the healthy control (p < 0.001) and DM group (p=0.002). A similar trend was observed when RDW was compared among the 3 groups with respect to age and gender. Logistic regression analysis has shown the OR of RDW was 3.791 (2.33-6.168; p < 0.001) against the control group and was 1.348 (0.997-1.823; p=0.047) against the DM group. CONCLUSION: RDW values were significantly elevated in DR patients, and an elevated RDW was associated with an increased incidence of DR in patients with DM.