Real-time model correction using Kalman filter for Raman-controlled cell culture processes

Raman spectroscopy has found extensive use in monitoring and controlling cell culture processes.In this context,the prediction accuracy of Raman-based models is of paramount importance.However,models established with data from manually fed-batch cultures often exhibit poor performance in Raman-controlled cultures.Thus,there is a need for effective methods to rectify these models.The objective of this paper is to investigate the efficacy of Kalman filter(KF)algorithm in correcting Raman-based models during cell culture.Initially,partial least squares(PLS)models for different components were constructed using data from manually fed-batch cultures,and the predictive performance of these models was compared.Subsequently,various correction methods including the PLS-KF-KF method proposed in this study were employed to refine the PLS models.Finally,a case study involving the auto-control of glucose concentration demonstrated the application of optimal model correction method.The results indicated that the original PLS models exhibited differential performance between manually fed-batch cultures and Raman-controlled cultures.For glucose,the root mean square error of prediction(RMSEP)of manually fed-batch culture and Raman-controlled culture was 0.23 and 0.40 g·L^(-1).With the implementation of model correction methods,there was a significant improvement in model performance within Raman-controlled cultures.The RMSEP for glucose from updating-PLS,KF-PLS,and PLS-KF-KF was 0.38,0.36 and 0.17 g·L^(-1),respectively.Notably,the proposed PLS-KF-KF model correction method was found to be more effective and stable,playing a vital role in the automated nutrient feeding of cell cultures.

Design and optimization of a greener sinomenine hydrochloride preparation process considering variations among different batches of the medicinal herb

The current methods used to industrially produce sinomenine hydrochloride involve several issues,including high solvent toxicity,long process flow,and low atomic utilization efficiency,and the greenness scores of the processes are below 65 points.To solve these problems,a new process using anisole as the extractant was proposed.Anisole exhibits high selectivity for sinomenine and can be connected to the subsequent water-washing steps.After alkalization of the medicinal material,heating extraction,water washing,and acidification crystallization were carried out.The process was modeled and optimized.The design space was constructed.The recommended operating ranges for the critical process parameters were 3.0–4.0 h for alkalization time,60.0–80.0℃ for extraction temperature,2.0–3.0(volume ratio)for washing solution amount,and 2.0–2.4 mol·L^(-1) for hydrochloric acid concentration.The new process shows good robustness because different batches of medicinal materials did not greatly impact crystal purity or sinomenine transfer rate.The sinomenine transfer rate was about 20%higher than that of industrial processes.The greenness score increased to 90 points since the novel process proposed in this research solves the problems of long process flow,high solvent toxicity,and poor atomic economy,better aligning with the concept of green chemistry.

A Single-Cell Landscape of Human Liver Transplantation Reveals a Pathogenic Immune Niche Associated with Early Allograft Dysfunction

Liver transplantation(LT)is the standard therapy for individuals afflicted with end-stage liver disease.Despite notable advancements in LT technology,the incidence of early allograft dysfunction(EAD)remains a critical concern,exacerbating the current organ shortage and detrimentally affecting the prognosis of recipients.Unfortunately,the perplexing hepatic heterogeneity has impeded characterization of the cellular traits and molecular events that contribute to EAD.Herein,we constructed a pioneering single-cell transcriptomic landscape of human transplanted livers derived from non-EAD and EAD patients,with 12 liver samples collected from 7 donors during the cold perfusion and portal reperfusion stages.Comparison of the 75231 cells of non-EAD and EAD patients revealed an EAD-associated immune niche comprising mucosal-associated invariant T cells,granzyme B^(+)(GZMB^(+))granzyme K^(+)(GZMK^(+))natural killer cells,and S100 calcium binding protein A12^(+)(S100A12^(+))neutrophils.Moreover,we verified this immune niche and its association with EAD occurrence in two independent cohorts.Our findings elucidate the cellular characteristics of transplanted livers and the EAD-associated pathogenic immune niche at the single-cell level,thus,offering valuable insights into EAD onset.

Guidelines for application of high-content screening in traditional Chinese medicine:concept,equipment,and troubleshooting

High-content screening(HCS)technology combines automated high-speed imaging hardware and single-cell quantitative analysis.It can greatly accelerate data acquisition in cellular fluorescence imaging and is a powerful research technique in traditional Chinese medicine(TCM).An increasing number of laboratories and platforms,including TCM laboratories,have begun utilizing HCS systems.However,this technology is still in its infancy in TCM research and there is a lack of sufficient experience with the associated concepts,instrument configurations,and analysis methods.To improve the understanding of HCS among researchers in the field of TCM,this paper summarizes the concept of HCS,software and hardware configuration,the overall research process,as well as common problems and related solutions of HCS in TCM research based on our team’s previous research experience,providing several research examples and an outlook on future perspectives,aiming to provide a technical guide for HCS in TCM research.

Factors Affecting the Adoption of E-Learning Systems in Public Higher Learning Institutions in Tanzania: A Case of Institute of Accountancy Arusha (IAA)

In most developing countries, governments attempt to enforce the movement from analogue to digital for all their sectors, from public to private. These technological advancements have been noted to bring necessary and unavoidable changes to businesses and learning environments. Higher learning institutions have adopted various e-learning systems to support learning, research, and publication activities to stay competitive in global academic systems. However, most public higher learning institutions in Tanzania lag behind in the adoption of these systems. Thus, research shows a failure of these institutions in utilising the full benefit that today’s Information and Communication Technology (ICT) can offer in learning environments. Thus, this study examines factors affecting the adoption of such a system in developing countries like Tanzania, taking the Institute of Accountancy Arusha (IAA) as a case study. The study used a mixed methodology where thematic and descriptive analysis was used to analyse both qualitative and quantitative research data. The study population was 187 teaching staff, a sample size of 126 was obtained, and 157 study participants were involved in the study. The study found that factors affecting the adoption of e-learning systems in public higher learning institutions in Tanzania include lack of ICT infrastructure, lack of technical and managerial support and lack of computers and e-learning knowledge among facilitators. Thus, the study recommended investments in adequate and reliable ICT facilities, high intermate speed and bandwidth, and policies that support e-learning and training programs about e-learning knowledge and use. Also, this study recommends the use of the Multi-Factors Adoption Model (MFAM11) for the successful adoption of an e-learning system in public higher learning institutions in Tanzania.

Information Systems Security Threats and Vulnerabilities: A Case of the Institute of Accountancy Arusha (IAA)

All modern computer users need to be concerned about information system security (individuals and organisations). Many businesses established various security structures to protect information system security from harmful occurrences by implementing security procedures, processes, policies, and information system security organisational structures to ensure data security. Despite all the precautions, information security remains a disaster in Tanzania’s learning institutions. The fundamental issue appears to be a lack of awareness of crucial information security factors. Various companies have different security issues due to differences in ICT infrastructure, implementations, and usage. The study focuses on identifying information system security threats and vulnerabilities in public higher learning institutions in Tanzania, particularly the Institute of Accountancy Arusha (IAA). The study involved all employees of IAA, academics, and other supporting staff, which totalled 302, and the sample size was 170. The study utilised a descriptive research design, where the quantitative methodology was used through a five-point Likert scale questionnaire, and found that key factors that affect the security of information systems at IAA include human factors, policy-related issues, work environment and demographic factors. The study proposed regular awareness and training programs;an increase in women’s awareness of information system security;proper policy creation and reviews every 4 years;promote actions that lessen information system security threats and vulnerabilities, and the creation of information system security policy documents independently from ICT policy.

Multimodal Identification by Transcriptomics and Multiscale Bioassays of Active Components in Xuanfeibaidu Formula to Suppress Macrophage-Mediated Immune Response

Xuanfeibaidu Formula (XFBD) is a Chinese medicine used in the clinical treatment of coronavirus disease 2019 (COVID-19) patients. Although XFBD has exhibited significant therapeutic efficacy in clinical practice, its underlying pharmacological mechanism remains unclear. Here, we combine a comprehensive research approach that includes network pharmacology, transcriptomics, and bioassays in multiple model systems to investigate the pharmacological mechanism of XFBD and its bioactive substances. High-resolution mass spectrometry was combined with molecular networking to profile the major active substances in XFBD. A total of 104 compounds were identified or tentatively characterized, including flavonoids, terpenes, carboxylic acids, and other types of constituents. Based on the chemical composition of XFBD, a network pharmacology-based analysis identified inflammation-related pathways as primary targets. Thus, we examined the anti-inflammation activity of XFBD in a lipopolysaccharide-induced acute inflammation mice model. XFBD significantly alleviated pulmonary inflammation and decreased the level of serum proinflammatory cytokines. Transcriptomic profiling suggested that genes related to macrophage function were differently expressed after XFBD treatment. Consequently, the effects of XFBD on macrophage activation and mobilization were investigated in a macrophage cell line and a zebrafish wounding model. XFBD exerts strong inhibitory effects on both macrophage activation and migration. Moreover, through multimodal screening, we further identified the major components and compounds from the different herbs of XFBD that mediate its anti-inflammation function. Active components from XFBD, including Polygoni cuspidati Rhizoma, Phragmitis Rhizoma, and Citri grandis Exocarpium rubrum, were then found to strongly downregulate macrophage activation, and polydatin, isoliquiritin, and acteoside were identified as active compounds. Components of Artemisiae annuae Herba and Ephedrae Herba were found to substantially inhibit endogenous macrophage migration, while the presence of ephedrine, atractylenolide I, and kaempferol was attributed to these effects. In summary, our study explores the pharmacological mechanism and effective components of XFBD in inflammation regulation via multimodal approaches, and thereby provides a biological illustration of the clinical efficacy of XFBD.

Dissecting the brain with spatially resolved multi-omics

Recent studies have highlighted spatially resolved multi-omics technologies,including spatial genomics,transcriptomics,proteomics,and metabolomics,as powerful tools to decipher the spatial heterogeneity of the brain.Here,we focus on two major approaches in spatial transcriptomics(next-generation sequencing-based technologies and image-based technologies),and mass spectrometry imaging technologies used in spatial proteomics and spatial metabolomics.Furthermore,we discuss their applications in neuroscience,including building the brain atlas,uncovering gene expression patterns of neurons for special behaviors,deciphering the molecular basis of neuronal communication,and providing a more comprehensive explanation of the molecular mechanisms underlying central nervous system disorders.However,further efforts are still needed toward the integrative application of multi-omics technologies,including the real-time spatial multi-omics analysis in living cells,the detailed gene profile in a whole-brain view,and the combination of functional verification.

Design and optimization of purification process of sinomenine hydrochloride

Sinomenine hydrochloride is generally produced from Caulis Sinomenii. At present, the purification process in industrial production suffers from large amount of solid waste, high solvent toxicity, and low sinomenine hydrochloride yield. In this study, a new purification process for sinomenine hydrochloride was proposed by using the extract obtained from acid extraction of Caulis Sinomenii as the starting material.The process included the following steps: alkalization, extraction, water washing, acid–water stripping,drying, and crystallization. 1-Heptanol was used as the extractant. The distribution coefficients of sinomenine and sinomenine hydrochloride in 1-heptanol–water system were 27.4 and 0.0167, respectively.The dissociation constants of sinomenine hydrochloride were 8.27 and 11.24, respectively. Process parameters of the new purification process were optimized with experimental design. The extractant1-heptanol and sinomenine hydrochloride in the crystallization mother solution can be recycled in the new process. The purity of the obtained sinomenine hydrochloride crystals exceeded 85%, and the yield was about 70%. Compared with current industrial processes, safer extractant, less solid waste, and higher sinomenine hydrochloride yield can be achieved using the new purification process of sinomenine hydrochloride provided in this study.

Human intestinal Caco-2 cell model to evaluate the absorption of 7-ketophytosterols and their effects on cholesterol transport

7-Ketophytosterols are the major oxidation products of phytosterols in foods, which have been associated with atherosclerosis. However, their absorption mechanism remains unclear. The aim of our work was to investigate the absorption mechanism of 7-ketophytosterols and their effects on the cholesterol transport using Caco-2 cell model. The absorption percentage of 7-ketositosterol and 7-ketocampesterol was 1.16%-1.68% and 1.18%-2.23% respectively in the Caco-2 model, which is higher than that of their parent phytosterols, but lower than cholesterol-d7. The apparent permeability of 7-ketositosterol and 7-ketocampesterol at 30 μmol/L in the basolateral(BL)-to-apical(AP)direction were 0.42-and 0.55-fold of that in the AP-to-BL direction, indicating an active intake in the permeation mechanism of 7-ketophytosterols. Ezetimibe could significantly inhibit the transport of 7-ketophytosterols(P < 0.05), which means that their transport depends on niemann-pick c1-like 1(NPC1L1)protein. The transport of cholesterol-d7 was significantly inhibited by 7-ketophytosterols(P < 0.05). Taken together, this study deepened our understanding of the absorption mechanism of common food-born 7-ketophytosterols and provides useful information on the inhibition of 7-ketophytosterols absorption.

Single-cell RNA sequencing reveals the dynamics of hepatic non-parenchymal cells in autoprotection against acetaminophen-induced hepatotoxicity

Gaining a better understanding of autoprotection against drug-induced liver injury(DILI)may provide new strategies for its prevention and therapy.However,little is known about the underlying mechanisms of this phenomenon.We used single-cell RNA sequencing to characterize the dynamics and functions of hepatic non-parenchymal cells(NPCs)in autoprotection against DILI,using acetaminophen(APAP)as a model drug.Autoprotection was modeled through pretreatment with a mildly hepatotoxic dose of APAP in mice,followed by a higher dose in a secondary challenge.NPC subsets and dynamic changes were identified in the APAP(hepatotoxicity-sensitive)and APAP-resistant(hepatotoxicity-resistant)groups.A chemokine(C-C motif)ligand 2^(+)endothelial cell subset almost disappeared in the APAP-resistant group,and an R-spondin 3^(+)endothelial cell subset promoted hepatocyte proliferation and played an important role in APAP autoprotection.Moreover,the dendritic cell subset DC-3 may protect the liver from APAP hepatotoxicity by inducing low reactivity and suppressing the autoimmune response and occurrence of inflammation.DC-3 cells also promoted angiogenesis through crosstalk with endothelial cells via vascular endothelial growth factor-associated ligand-receptor pairs and facilitated liver tissue repair in the APAP-resistant group.In addition,the natural killer cell subsets NK-3 and NK-4 and the Sca-1^(-)CD62L^(+)natural killer T cell subset may promote autoprotection through interferon-γ-dependent pathways.Furthermore,macrophage and neutrophil subpopulations with anti-inflammatory phenotypes promoted tolerance to APAP hepatotoxicity.Overall,this study reveals the dynamics of NPCs in the resistance to APAP hepatotoxicity and provides novel insights into the mechanism of autoprotection against DILI at a high resolution.

High-throughput transcriptional profiling of perturbations by Panax ginseng saponins and Panax notoginseng saponins using TCM-seq

Panax ginseng(PG)and Panax notoginseng(PN)are highly valuable Chinese medicines(CM).Although both CMs have similar active constituents,their clinical applications are clearly different.Over the past decade,RNA sequencing(RNA-seq)analysis has been employed to investigate the molecular mechanisms of extracts or monomers.However,owing to the limited number of samples in standard RNA-seq,few studies have systematically compared the effects of PG and PN spanning multiple conditions at the transcriptomic level.Here,we developed an approach that simultaneously profiles transcriptome changes for multiplexed samples using RNA-seq(TCM-seq),a high-throughput,low-cost workflow to molecularly evaluate CM perturbations.A species-mixing experiment was conducted to illustrate the accuracy of sample multiplexing in TCM-seq.Transcriptomes from repeated samples were used to verify the robustness of TCM-seq.We then focused on the primary active components,Panax notoginseng saponins(PNS)and Panax ginseng saponins(PGS)extracted from PN and PG,respectively.We also characterized the transcriptome changes of 10 cell lines,treated with four different doses of PNS and PGS,using TCM-seq to compare the differences in their perturbing effects on genes,functional pathways,gene modules,and molecular networks.The results of transcriptional data analysis showed that the transcriptional patterns of various cell lines were significantly distinct.PGS exhibited a stronger regulatory effect on genes involved in cardiovascular disease,whereas PNS resulted in a greater coagulation effect on vascular endothelial cells.This study proposes a paradigm to comprehensively explore the differences in mechanisms of action between CMs based on transcriptome readouts.

A Blockchain-Assisted Distributed Edge Intelligence for Privacy-Preserving Vehicular Networks

The enormous volume of heterogeneous data fromvarious smart device-based applications has growingly increased a deeply interlaced cyber-physical system.In order to deliver smart cloud services that require low latency with strong computational processing capabilities,the Edge Intelligence System(EIS)idea is now being employed,which takes advantage of Artificial Intelligence(AI)and Edge Computing Technology(ECT).Thus,EIS presents a potential approach to enforcing future Intelligent Transportation Systems(ITS),particularly within a context of a Vehicular Network(VNets).However,the current EIS framework meets some issues and is conceivably vulnerable tomultiple adversarial attacks because the central aggregator server handles the entire systemorchestration.Hence,this paper introduces the concept of distributed edge intelligence,combining the advantages of Federated Learning(FL),Differential Privacy(DP),and blockchain to address the issues raised earlier.By performing decentralized data management and storing transactions in immutable distributed ledger networks,the blockchain-assisted FL method improves user privacy and boosts traffic prediction accuracy.Additionally,DP is utilized in defending the user’s private data from various threats and is given the authority to bolster the confidentiality of data-sharing transactions.Our model has been deployed in two strategies:First,DP-based FL to strengthen user privacy by masking the intermediate data during model uploading.Second,blockchain-based FL to effectively construct secure and decentralized traffic management in vehicular networks.The simulation results demonstrated that our framework yields several benefits for VNets privacy protection by forming a distributed EIS with privacy budget(ε)of 4.03,1.18,and 0.522,achieving model accuracy of 95.8%,93.78%,and 89.31%,respectively.

The“Top 50 High Impact Researches of Traditional Medicine”published in 2021

In recent years,significant progress has been achieved in both basic and clinical research within the field of traditional medicine,garnering increasing attention worldwide.To further promote a high-quality and international development of traditional medicine,the editorial board of Acupuncture and Herbal Medicine provided a collection of the“Top 50 High-impact Researches of Traditional Medicine”published in 2021 through objective indicators and a strict selection process.The findings of the selected articles have a significant academic influence and possess considerable academic value both nationally and internationally.The selected articles cover a wide range of topics,including clinical research,acupuncture,pharmacology,chemistry,biosynthesis,medicinal plant resources,and new formulation and drug delivery system research on traditional medicine.Therefore,this article outlines the selection process of the top 50 high-impact research articles,analyzes their research characteristics,and provides a brief summary of their new findings and perspectives in the field of traditional medicine.

A High-Performance Liquid Chromatography Method for the Simultaneous Determination of Five Index Components in Danhong Injection

The purpose of this study was to establish a high-performance liquid chromatography (HPLC) method for the simultaneous determination of sodium danshensu, protocatechuic aldehyde, rosmarinic acid, salvianolic acid B, and 4-coumaric acid in Danhong injection. The chromatographic method employed was as follows: the column was a Welch Ultimate XB-C18 column (250 mm × 4.6 mm, 10 μm), the mobile phase was a gradient elution of 0.4% formic acid aqueous solution (A) and acetonitrile (B), the detection wavelengths were 280 nm for sodium danshensu, protocatechuic aldehyde, and salvianolic acid B and 326 nm for 4-coumaric acid and rosmarinic acid, the sample volume was 10 μL, the flow rate was 1.0 mL/min, and the column temperature was 35°C. This method can realize the separation and determination of sodium danshensu, protocatechuic aldehyde, rosmarinic acid, salvianolic acid B, and 4-coumaric acid within 50 minutes. The linear relationships of the five peak areas and their concentrations are good (R2> 0.9997). The precision RSD values are all less than 1.0%. The reproducibility RSD values are all less than 1.3%. The stability RSD values are all less than 2.2%. The recovery values ranged from 92.4% to 99.4%. This method is simple, accurate, and reproducible. It can be used for the determination of sodium danshensu, protocatechuic aldehyde, rosmarinic acid, salvianolic acid B, and 4-coumaric acid in Danhong injection.

Modeling of degradation kinetics of Salvianolic acid B at different temperatures and pH values

In this work,the effects of degradation time,temperature,and pH value on the degradation of Salvianolic acid B in aqueous solution were determined.Higher pH values,higher extraction temperature,and longer extraction time led to more degradation of Salvianolic acid B.Danshensu concentration increased as Salvianolic acid B degraded.A mechanism model was developed considering the degradation of Salvianolic acid E and lithospermic acid,which were two degradation products of Salvianolic acid B.The reverse reactions of Salvianolic acid B degradation were also considered.Degradation kinetic constants were calibrated.The degradation kinetics of Salvianolic acid B,lithospermic acid,and Danshensu in a Salvia miltiorrhiza extract aqueous solution were predicted using the mechanism model.The predicted concentrations agreed well with the experimental results.This model was developed using degradation data obtained from simple composition systems,but it can be applied in a complex botanical mixture with high prediction accuracy.

Safety Research in Traditional Chinese Medicine: Methods, Applications, and Outlook

Traditional Chinese medicine (TCM) is a medical system that has collected and summarized abundant clinical experience over its long history of more than 2000 years. However, the frequent occurrence of TCM-induced adverse reactions has hindered the modernization and internationalization of TCM, while attracting increasing attention from around the world. Unlike chemical drugs and biological agents, the difficulties involved in research on the toxicity and safety of TCM mainly include the complexity of its components and the unpredictability of drug–body interactions. Much of TCM, which has overall therapeutic effects, has the typical mechanisms of multiple components, multiple pathways, and multiple targets. While considering the gradualness and unpredictability of TCM toxicity, the ambiguity of toxicants and safe dosage, and individual differences during long-term TCM administration, we have systematically established key techniques for the toxicity assessment of TCM. These techniques mainly include TCM toxicity discovery in an early phase, based on a combination of drug toxicology genomics and metabolomics;methods to identify dose–toxicity relationships in TCM;and integrated techniques for the exploration of TCM interactions, such as fast-screening tests based on drug-metabolizing enzymes and receptor pathways. In particular, we have developed a new technical system for TCM safety evaluation using molecular toxicology, which has been validated well in research on TCM compatibility contraindication, quality control, and allergen discovery. The application of this key technical platform is introduced here in detail. This application includes model organisms, toxicant biomarkers, a magnetic suspension technique, and the application of network toxicology and computational toxicology in research on the toxicity of Fructus toosendan, Semen cassiae, Polygonum multiflorum, and Fructus psoraleae.

Association of residual feed intake with abundance of ruminal bacteria and biopolymer hydrolyzing enzyme activities during the peripartal period and early lactation in Holstein dairy cows

Background: Residual feed intake(RFI) in dairy cattle typically calculated at peak lactation is a measure of feed efficiency independent of milk production level. The objective of this study was to evaluate differences in ruminal bacteria, biopolymer hydrolyzing enzyme activities, and overall performance between the most-and the leastefficient dairy cows during the peripartal period. Twenty multiparous Holstein dairy cows with daily ad libitum access to a total mixed ration from d-10 to d 60 relative to the calving date were used. Cows were classified into most-efficient(i.e. with low RFI, n = 10) and least-efficient(i.e. with high RFI, n = 10) based on a linear regression model involving dry matter intake(DMI), fat-corrected milk(FCM), changes in body weight(BW), and metabolic BW.Results: The most-efficient cows had ~ 2.6 kg/d lower DMI at wk 4, 6, 7, and 8 compared with the least-efficient cows. In addition, the most-efficient cows had greater relative abundance of total ruminal bacterial community during the peripartal period. Compared with the least-efficient cows, the most-efficient cows had 4-fold greater relative abundance of Succinivibrio dextrinosolvens at d-10 and d 10 around parturition and tended to have greater abundance of Fibrobacter succinogenes and Megaspheara elsdenii. In contrast, the relative abundance of Butyrivibrio proteoclasticus and Streptococcus bovis was lower and Succinimonas amylolytica and Prevotella bryantii tended to be lower in the most-efficient cows around calving. During the peripartal period, the most-efficient cows had lower enzymatic activities of cellulase, amylase, and protease compared with the least-efficient cows.Conclusions: The results suggest that shifts in ruminal bacteria and digestive enzyme activities during the peripartal period could, at least in part, be part of the mechanism associated with better feed efficiency in dairy cows.

Residual feed intake in beef cattle and its association with carcass traits, ruminal solid-fraction bacteria, and epithelium gene expression

Background: Residual feed intake(RFI) describes an animal’s feed efficiency independent of growth performance.The objective of this study was to determine differences in growth performance, carcass traits, major bacteria attached to ruminal solids-fraction, and ruminal epithelium gene expression between the most-efficient and the least-efficient beef cattle. One-hundred and forty-nine Red Angus cattle were allocated to three contemporary groups according to sex and herd origin. Animals were fed a finishing diet in confinement for 70 d to determine the RFI category for each. Within each group, the two most-efficient(n = 6; RFI coefficient =-2.69 ± 0.58 kg dry matter intake(DMI)/d) and the two least-efficient animals(n = 6; RFI coefficient = 3.08 ± 0.55 kg DMI/d) were selected. Immediately after slaughter, ruminal solids-fraction and ruminal epithelium were collected for bacteria relative abundance and epithelial gene expression analyses, respectively, using real-time PCR.Results: The most-efficient animals consumed less feed(P = 0.01; 5.03 kg less DMI/d) compared with the leastefficient animals. No differences(P > 0.10) in initial body weight(BW), final BW, and average daily gain(ADG) were observed between the two RFI classes. There were no significant RFI × sex effects(P > 0.10) on growth performance.Compared with the least-efficient group, hot carcass weight(HCW), ribeye area(REA), and kidney, pelvic, and heart fat(KPH) were greater(P ≤ 0.05) in the most-efficient cattle. No RFI × sex effect(P > 0.10) for carcass traits was detected between RFI groups. Of the 10 bacterial species evaluated, the most-efficient compared with least efficient cattle had greater(P ≤ 0.05) relative abundance of Eubacterium ruminantium, Fibrobacter succinogenes, and Megasphaera elsdenii, and lower(P ≤ 0.05) Succinimonas amylolytica and total bacterial density. No RFI × sex effect on ruminal bacteria was detected between RFI groups. Of the 34 genes evaluated in ruminal epithelium, the mostefficient cattle had greater(P ≤ 0.05) abundance of genes involved in VFA absorption, metabolism, ketogenesis, and immune/inflammation-response. The RFI × sex interactions indicated that responses in gene expression between RFI groups were due to differences in sex. Steers in the most-efficient compared with least-efficient group had greater(P ≤ 0.05) expression of SLC9 A1, HIF1 A, and ACO2. The most-efficient compared with least-efficient heifers had greater(P ≤ 0.05) m RNA expression of BDH1 and lower expression(P ≤ 0.05) of SLC9 A2 and PDHA1.Conclusions: The present study revealed that greater feed efficiency in beef cattle is associated with differences in bacterial species and transcriptional adaptations in the ruminal epithelium that might enhance nutrient delivery and utilization by tissues. The lack of RFI × sex interaction for growth performance and carcass traits indicates that sex may not play a major role in improving these phenotypes in superior RFI beef cattle. However, it is important to note that this result should not be considered a solid biomarker of efficient beef cattle prior to further examination due to the limited number of heifers compared with steers used in the study.

An ultra-robust fingerprinting method for quality assessment of traditional Chinese medicine using multiple reaction monitoring mass spectrometry

Chromatographic fingerprinting has been perceived as an essential tool for assessing quality and chemical equivalence of traditional Chinese medicine.However,this pattern-oriented approach still has some weak points in terms of chemical coverage and robustness.In this work,we proposed a multiple reaction monitoring(MRM)-based fingerprinting method in which approximately 100 constituents were simultaneously detected for quality assessment.The derivative MRM approach was employed to rapidly design MRM transitions independent of chemical standards,based on which the large-scale fingerprinting method was efficiently established.This approach was exemplified on QiShenYiQi Pill(QSYQ),a traditional Chinese medicine-derived drug product,and its robustness was systematically evaluated by four indices:clustering analysis by principal component analysis,similarity analysis by the congruence coefficient,the number of separated peaks,and the peak area proportion of separated peaks.Compared with conventional ultraviolet-based fingerprints,the MRM fingerprints provided not only better discriminatory capacity for the tested normal/abnormal QSYQ samples,but also higher robustness under different chromatographic conditions(i.e.,flow rate,apparent pH,column temperature,and column).The result also showed for such large-scale fingerprints including a large number of peaks,the angle cosine measure after min-max normalization was more suitable for setting a decision criterion than the unnormalized algorithm.This proof-of-concept application gives evidence that combining MRM technique with proper similarity analysis metrices can provide a highly sensitive,robust and comprehensive analytical approach for quality assessment of traditional Chinese medicine.