The areas of Research Ethics (RE) and Research Integrity (RI) are rapidly evolving. Cases of research misconduct, other transgressions related to RE and RI, and forms of ethically questionable behaviors have been frequently published. The objective of this scoping review was to collect RE and RI cases, analyze their main characteristics, and discuss how these cases are represented in the scientific literature.The search included cases involving a violation of, or misbehavior, poor judgment, or detrimental research practice in relation to a normative framework. A search was conducted in PubMed, Web of Science, SCOPUS, JSTOR, Ovid, and Science Direct in March 2018, without language or date restriction. Data relating to the articles and the cases were extracted from case descriptions.A total of 14,719 records were identified, and 388 items were included in the qualitative synthesis. The papers contained 500 case descriptions. After applying the eligibility criteria, 238 cases were included in the analysis. In the case analysis, fabrication and falsification were the most frequently tagged violations (44.9%). The non-adherence to pertinent laws and regulations, such as lack of informed consent and REC approval, was the second most frequently tagged violation (15.7%), followed by patient safety issues (11.1%) and plagiarism (6.9%). 80.8% of cases were from the Medical and Health Sciences, 11.5% from the Natural Sciences, 4.3% from Social Sciences, 2.1% from Engineering and Technology, and 1.3% from Humanities. Paper retraction was the most prevalent sanction (45.4%), followed by exclusion from funding applications (35.5%).Case descriptions found in academic journals are dominated by discussions regarding prominent cases and are mainly published in the news section of journals. Our results show that there is an overrepresentation of biomedical research cases over other scientific fields compared to its proportion in scientific publications. The cases mostly involve fabrication, falsification, and patient safety issues. This finding could have a significant impact on the academic representation of misbehaviors. The predominance of fabrication and falsification cases might diverge the attention of the academic community from relevant but less visible violations, and from recently emerging forms of misbehaviors.The online version contains supplementary material available at 10.1186/s12910-021-00620-8. There has been an increase in academic interest in research ethics (RE) and research integrity (RI) over the past decade. This is due, among other reasons, to the changing research environment with new and complex technologies, increased pressure to publish, greater competition in grant applications, increased university-industry collaborative programs, and growth in international collaborations . In addiThere is a growing body of published RE and RI cases, which may contribute to public attitudes regarding both science and scientists . Differewww.embassy.science). Two separate analyses have been conducted. The first analysis uses identified research articles to explore how the literature presents cases of RE and RI, in relation to the year of publication, country, article genre, and violation involved. The second analysis uses the cases extracted from the literature in order to characterize the cases and analyze them concerning the violations involved, sanctions, and field of science.Analyses of RE and RI cases often influence policies on responsible conduct of research . Moreovehttps://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5bde92120&appId=PPGMS.This scoping review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and PRISMA Extension for Scoping Reviews (PRISMA-ScR). The full protocol was pre-registered and it is available at Articles with non-fictional case(s) involving a violation of, or misbehavior, poor judgment, or detrimental research practice in relation to a normative framework, were included. Cases unrelated to scientific activities, research institutions, academic or industrial research and publication were excluded. Articles that did not contain a substantial description of the case were also excluded.A normative framework consists of explicit rules, formulated in laws, regulations, codes, and guidelines, as well as implicit rules, which structure local research practices and influence the application of explicitly formulated rules. Therefore, if a case involves a violation of, or misbehavior, poor judgment, or detrimental research practice in relation to a normative framework, then it does so on the basis of explicit and/or implicit rules governing RE and RI practice.A search was conducted in PubMed, Web of Science, SCOPUS, JSTOR, Ovid, and Science Direct in March 2018, without any language or date restrictions. Two parallel searches were performed with two sets of medical subject heading (MeSH) terms, one for RE and another for RI. The parallel searches generated two sets of data thereby enabling us to analyze and further investigate the overlaps in, differences in, and evolution of, the representation of RE and RI cases in the academic literature. The terms used in the first search were: (("research ethics") AND ). The terms used in the parallel search were: (("research integrity") AND ). The search strategy’s validity was tested in a pilot search, in which different keyword combinations and search strings were used, and the abstracts of the first hundred hits in each database were read . Articles that could potentially meet the inclusion criteria were identified. After independent reading, the three contributors compared their results to determine which studies were to be included in the next stage. In case of a disagreement, items were reassessed in order to reach a consensus. Subsequently, qualified items were read in full.Data extraction processes were divided by three assessors . Each list of extracted data generated by one assessor was cross-checked by the other two. In case of any inconsistencies, the case was reassessed to reach a consensus. The following categories were employed to analyze the data of each extracted item (where available): (I) author(s); (II) title; (III) year of publication; (IV) country (according to the first author's affiliation); (V) article genre; (VI) year of the case; (VII) country in which the case took place; (VIII) institution(s) and person(s) involved; (IX) field of science (FOS-OECD classification); (X) typTwo sets of data were created after the data extraction process. One set was used for the analysis of articles and their representation in the literature, and the other set was created for the analysis of cases. In the set for the analysis of articles, all eligible items, including duplicate cases  were included. The aim was to understand the historical aspects of violations reported in the literature as well as the paper genre in which cases are described and discussed. For this set, the variables of the year of publication (III); country (IV); article genre (V); and types of violation (X) were analyzed.For the analysis of cases, all duplicated cases and cases that did not contain enough information about particularities to differentiate them from others  were excluded. In this set, prominent cases (i.e. those found in more than one paper) were listed only once, generating a set containing solely unique cases. These additional exclusion criteria were applied to avoid multiple representations of cases. For the analysis of cases, the variables: (VI) year of the case; (VII) country in which the case took place; (VIII) institution(s) and person(s) involved; (IX) field of science (FOS-OECD classification); (X) types of violation; (XI) case details; and (XII) consequences for persons or institutions involved in the case were considered.We used ten categories to capture the differences in genre. We included a case description in a “news” genre if a case was published in the news section of a scientific journal or newspaper. Although we have not developed a search strategy for newspaper articles, some of them (e.g. New York Times) are indexed in scientific databases such as Pubmed. The same method was used to allocate case descriptions to “editorial”, “commentary”, “misconduct notice”, “retraction notice”, “review”, “letter” or “book review”. We applied the “case analysis” genre if a case description included a normative analysis of the case. The “educational” genre was used when a case description was incorporated to illustrate RE and RI guidelines or institutional policies.For the extraction process, we used the articles’ own terminology when describing violations/ethical issues involved in the event  to tag each article. In case the terminology was incompatible with the case description, other categories were added to the original terminology for the same case. Subsequently, the resulting list of terms was standardized using the list of major and minor misbehaviors developed by Bouter and colleagues . This liA total of 11,641 records were identified through the RE search and 3078 in the RI search. The results of the parallel searches were combined and the duplicates removed. The remaining 10,556 records were screened, and at this stage, 9750 items were excluded because they did not fulfill the inclusion criteria. 806 items were selected for full-text reading. Subsequently, 388 articles were included in the qualitative synthesis  duplicates were excluded, and 56 (11.2%) cases were excluded for not providing enough information to distinguish them from other cases, resulting in 238 eligible cases.The categories used to classify the violations include those that pertain to the different kinds of scientific misconduct , detrimental research practices , and “other misconduct” . Each cFigure The articles were mostly classified into “news” (33.0%), followed by “case analysis” (20.9%), “editorial” (12.1%), “commentary” (10.8%), “misconduct notice” (10.3%), “retraction notice” 6.4%), “letter” (3.6%), “educational paper” (1.3%), “review” (1%), and “book review” (0.3%)  could not be classified due to insufficient information. Where information was available, 80.8% of cases were from the Medical and Health Sciences, 11.5% from the Natural Sciences, 4.3% from Social Sciences, 2.1% from Engineering and Technology, and 1.3% from Humanities  involved paper retraction, followed by exclusion from funding applications (35.5%). Table .Table 2FRE and RI cases have been increasingly discussed publicly, affecting public attitudes towards scientists and raising awareness about ethical issues, violations, and their wider consequences . DiffereWe collected and analyzed 500 detailed case descriptions from 388 articles and our results show that they mostly relate to extensively discussed and notorious cases. Approximately half of all included cases was mentioned in at least two different articles, and the top ten most commonly mentioned cases were discussed in 132 articles.The prominence of certain cases in the literature, based on the number of duplicated cases we found (e.g. Hwang case), can be explained by the type of article in which cases are discussed and the type of violation involved in the case. In the article genre analysis, 33% of the cases were described in the news section of scientific publications. Our findings show that almost all article genres discuss those cases that are new and in vogue. Once the case appears in the public domain, it is intensely discussed in the media and by scientists, and some prominent cases have been discussed for more than 20 years Table . MiscondThe analysis of violations/ethical issues shows the dominance of fabrication and falsification cases and explains the high prevalence of prominent cases. Non-adherence to laws and regulations  was the second most prevalent issue, followed by patient safety, plagiarism, and conflicts of interest. The prevalence of the five most tagged violations in the case analysis was higher than the prevalence found in the analysis of articles that involved the same violations. The only exceptions are fabrication and falsification cases, which represented 45% of the tagged violations in the analysis of cases, and 59.1% in the article analysis. This disproportion shows a predilection for the publication of discussions related to fabrication and falsification when compared to other serious violations. Complex cases involving these types of violations make good headlines and this follows a custom pattern of writing about cases that catch the public and media’s attention . The wayA notable increase in RE and RI cases occurred in the 1990s, with a gradual increase until approximately 2006. This result is in agreement with studies that evaluated paper retractions , 29. AltThe countries from which most cases were reported were the USA (59.6%), the UK (9.8%), Canada (6.0%), Japan (5.5%), and China (2.1%). When analyzed by continent, the highest percentage of cases took place in North America, followed by Europe, Asia, Oceania, Latin America, and Africa. The predominance of cases from the USA is predictable, since the country publishes more scientific articles than any other country, with 21.8% of the total documents, according to SCImago . HoweverThe results show that 80.8% of reported cases occurred in the medical and health sciences whilst only 1.3% occurred in the humanities. This disciplinary difference has also been observed in studies on research integrity climates. A study conducted by Haven and colleagues,  associatIn the analysis of violations, the cases were categorized into major and minor misbehaviors. Most cases involved data fabrication and falsification, followed by cases involving non-adherence to laws and regulations, patient safety, plagiarism, and conflicts of interest. When classified by categories, 12.5% of the tagged violations involved issues in the study design, 16.4% in data collection, 56.0% in reporting, and 15.1% involved collaboration issues. Approximately 80% of the tagged violations involved serious research misbehaviors, based on the ranking of research misbehaviors proposed by Bouter and colleagues. However, as demonstrated in a meta-analysis by Fanelli 2009), most self-declared cases involve questionable research practices. In the meta-analysis, 33.7% of scientists admitted questionable research practices, and 72% admitted when asked about the behavior of colleagues. This finding contrasts with an admission rate of 1.97% and 14.12% for cases involving fabrication, falsification, and plagiarism. However, Fanelli’s meta-analysis does not include data about research misbehaviors in its wider sense but focuses on behaviors that bias research results . In our study, the majority of cases involved FFP (66.4%). Overrepresentation of some types of violations, and underrepresentation of others, might lead to misguided efforts, as cases that receive intense publicity eventually influence policies relating to scientific misconduct and RI [09, most The five most prevalent outcomes were paper retraction, followed by exclusion from funding applications, exclusion from service or position, dismissal and suspension, and paper correction. This result is similar to that found by Redman and Merz , who colThe lack of publicly available summaries of misconduct investigations makes it difficult to share experiences and evaluate the effectiveness of policies and training programs. Publicizing scientific misconduct can have serious consequences and creates a stigma around those involved in the case. For instance, publicized allegations can damage the reputation of the accused even when they are later exonerated . Thus, fOne of the possible limitations of our study may be our search strategy. Although we have conducted pilot searches and sensitivity tests to reach the most feasible and precise search strategy, we cannot exclude the possibility of having missed important cases. Furthermore, the use of English keywords was another limitation of our search. Since most investigations are performed locally and published in local repositories, our search only allowed us to access cases from English-speaking countries or discussed in academic publications written in English. Additionally, it is important to note that the published cases are not representative of all instances of misconduct, since most of them are never discovered, and when discovered, not all are fully investigated or have their findings published. It is also important to note that the lack of information from the extracted case descriptions is a limitation that affects the interpretation of our results. In our review, only 25 retraction notices contained sufficient information that allowed us to include them in our analysis in conformance with the inclusion criteria. Although our search strategy was not focused specifically on retraction and misconduct notices, we believe that if sufficiently detailed information was available in such notices, the search strategy would have identified them.Case descriptions found in academic journals are dominated by discussions regarding prominent cases and are mainly published in the news section of journals. Our results show that there is an overrepresentation of biomedical research cases over other scientific fields when compared with the volume of publications produced by each field. Moreover, published cases mostly involve fabrication, falsification, and patient safety issues. This finding could have a significant impact on the academic representation of ethical issues for RE and RI. The predominance of fabrication and falsification cases might diverge the attention of the academic community from relevant but less visible violations and ethical issues, and recently emerging forms of misbehaviors.Additional file 1. Pilot search and search strategy.Additional file 2. List of Major and minor misbehavior items :17. https://doi.org/10.1186/s41073-016-0024-5).Additional file 3. Table containing the number and percentage of countries included in the analysis of articles.Additional file 4. Table containing the number and percentage of countries included in the analysis of the cases.


In order to quickly, nondestructively, and effectively distinguish red jujube varieties, based on the combination of fuzzy theory and improved LDA (iLDA), fuzzy improved linear discriminant analysis (FiLDA) algorithm was proposed to classify near-infrared reflectance (NIR) spectra of red jujube samples. FiLDA shows performs better than iLDA in dealing with NIR spectra containing noise. Firstly, the portable NIR spectrometer was employed to gather the NIR spectra of five kinds of red jujube, and the initial NIR spectra were pretreated by standard normal variate transformation (SNV), multiplicative scatter correction (MSC), Savitzky-Golay smoothing (S-G smoothing), mean centering (MC) and Savitzky-Golay filter (S-G filter). Secondly, the high-dimensional spectra were processed for dimension reduction by principal component analysis (PCA). Then, linear discriminant analysis (LDA), iLDA and FiLDA were applied to extract features from the NIR spectra, respectively. Finally, K nearest neighbor (KNN) served as a classifier for the classification of red jujube samples. The highest classification accuracy of this identification system for red jujube, by using FiLDA and KNN, was 94.4%. These results indicated that FiLDA combined with NIR spectroscopy was an available method for identifying the red jujube varieties and this method has wide application prospects. Red jujube is a kind of agricultural product with a long history. It has caught the fascination of people all over the world and is widely planted in China. Red jujube is rich in a variety of nutrients that are beneficial to the human body, including sugars, fats, organic acids, amino acids, vitamins, flavonoids, and a variety of trace elements, which can prevent cancer, cardiovascular and cerebrovascular diseases . For difSome traditional identification methods of red jujube varieties have been extensively employed. Professional jujube discriminators can identify the type of red jujube by its shape, colour, and clarity. However, many professionals are vulnerable to the environment and physical state. Furthermore, it also takes plenty of time and money to train a professional red jujube appraiser. In recent years, domestic and foreign researchers actively established some methods for identifying red jujube varieties. For example, Wang et al. explored the electrical characteristics of red jujube fruits for variety identification in 2014 .At present, NIR spectroscopy technology has been quite mature with the emergence of several new types of spectral instruments, and there it has many advantages: fast, low cost, and other advantages ,7,8,9,10k-nearest neighbor algorithm (FKNN) to face recognition and obtained high accuracy. Xie et al. [Fuzzy recognition is an analytical method which uses fuzzy mathematics theory to solve related problems. Compared with other pattern recognition methods, fuzzy recognition has the advantages of good stability and can accurately describe the diversity of sample information. At present, fuzzy set theory has been used in many fields. Yan et al.  combinede et al.  applied e et al. . MoreoveLDA is a supervised pattern recognition technology and it is also an effective feature extraction and dimensionality reduction technology . BeveragThe purpose of this experiment was to combine fuzzy set theory and feature extraction algorithms to establish a classification model for identifying the red jujube varieties. The experimental steps were described as follows: (1) employ a portable NIR spectrometer to collect the spectra of red jujube samples; (2) preprocess the spectral data, and then use feature extraction algorithms to extract features from the data; (3) utilize KNN to build the identification model of red jujube samples, in order to realize the rapid identification of different red jujube varieties.There are five varieties of red jujube samples which come from five production areas  in China. That is, one variety corresponds to one production area. Each variety has 60 samples, so a total of 300 samples were selected. Subsequently, all of the red jujube samples were divided into training and test samples in a certain proportion. The selection of red jujube samples was needed to meet the following requirements: the size , weight (10–20 g) and maturity of red jujube which came from the same variety had little difference. Meanwhile, the experimenters ensured that the surface of the red jujube was clean and free from obvious defects.The NIR-M-R2 spectrometer , a portable spectrometer, was employed to collect NIR spectral data of red jujube samples. It has a wavelength range of 900–1700 nm, a signal-to-noise ratio of 6000:1, the InGaAs detector, and a slit size of 1.8 × 0.025 mm. During the whole collection process, the experimental temperature and relative humidity were kept at about 25 °C and 50–60%, respectively. Before collecting the NIR spectral data, the spectrometer must be preheated for one hour. The wavelength range of the collected NIR spectra was 900–1700 nm, and the resolution ratio was 10 nm. The collected NIR spectra of red jujube were the 228-dimensional data. Each red jujube sample was scanned three times by the spectrometer along around the equator, and the final data were the average of the three test results. FiLDA can deal with noisy data better than LDA and iLDA, so we used the whole range of the spectra to show this advantage of FiLDA. The final spectrogram was displayed in The original spectra were easily influenced by the physical properties of the samples. The data shown in In order to get the best experimental results, we employed five pre-processing methods which include MSC, SNV, S-G smoothing, MC and S-G filter ,41 to prThe dimensionality of the collected red jujube NIR spectra was 228. These initial NIR spectra of red jujube samples included some redundant information and noise data, which could increase the difficulty of classification and reduce the accuracy of classification. In order to obtain the effective information of NIR spectra, it was necessary to extract multiple eigenvalues for analysis. However, excessive eigenvalues would not only affect the subsequent spectral analysis but also increase the difficulty of the experiment. The purpose of dimensionality reduction is to find characteristic value which can directly mirror the discrepancy of NIR spectra. PCA is a widely used analytical method, which can be employed to reduce dimension and remove redundant information ,43. MeanLDA is a traditional algorithm to reduce the spectral dimension . In the wS when the eigenvalues are zero [iLDA is also an algorithm for feature extraction and it can extract the identification information in the matrix of are zero .D; Output: transformation matrix W):In this study, iLDA algorithm had two purposes: on the one hand, since the NIR spectra of red jujube was the high-dimensional data, iLDA was employed to deal with spectral data. On the other hand, it could also extract characteristic information from spectral data. Then, the steps of the iLDA are listed as follows :The steps of the FiLDA are listed as follows .In this study, the wavelength scope of the collected NIR spectra of red jujube was 900–1700 nm. The NIR spectra contained a lot of characteristic functional group information as shown in 1 = 133.189, λ2 = 7.711, λ3 = 7.258, λ4 = 0.425, λ5 = 0.117, λ6 = 0.062, λ7 = 0.029. Since the first 3 principal components  accounted for 99.6% of the total square deviation, they not only preserved the characteristic information of the NIR spectrum data but also eliminated the redundant information. Therefore, the three-dimensional feature space of NIR spectral data of red jujube was established. The data cannot be used directly after pre-processing because the spectral data contained a lot of repetitive information. This phenomenon was unfavourable for the classification of red jujube varieties. Therefore, in order to obtain the principal components of the spectrum of red jujube samples and remove the redundant information, the spectral dimension must be reduced first . In thisLDA scores plot of vectors with DV1, DV2, and DV3 were shown in iLDA extracted discriminant information from the 7-dimensional spectral data. A total of 300 red jujube samples were divided into the training set  and the test set . After the training set was processed by iLDA to produce 3 optimal discriminant vectors , the 7-dimensional spectral data of 125 test samples were projected to DV1, DV2 and DV3. In this section, FiLDA was applied to extract feature information of the NIR spectral data after PCA dimension reduction. All of the parameters were as follows: the fuzzy weight parameter ith sample jth class, we could confirm the ith sample belonged to the jth class.The initial fuzzy membership values of FiLDA were displayed in The pre-processing method and feature extraction algorithm were S-G filter and LDA, respectively, and the classification accuracy of the KNN was 75.2%. There were 14 samples from Shanxi misclassified as those from Henan and there were also 4 samples from Xinjiang misclassified as those from Shanxi. There was also 11 sample from Hebei misclassified as that from Xinjiang, and there were also 2 samples from Gansu misclassified as those from Hebei. The pre-processing method and feature extraction algorithm were S-G filter and FiLDA, respectively, and the classification accuracy of the KNN reached 94.4%. There were 2 samples from Hebei misclassified as those from Shanxi, and there were also 2 samples from Gansu misclassified as those from Hebei. There was also about 1 sample from Shanxi misclassified as that from Henan and there was also 1 sample from Xinjiang misclassified as that from Shanxi. It can prove that FiLDA can classify red jujube varieties and has a good classification effect. At the same time, it was apparent that the classification accuracies of LDA were generally not as good as those of iLDA and FiLDA when using the same pre-processing methods.The NIR spectral data were collected by the NIR-M-R2 spectrometer, and then spectral data were processed by S-G filter, PCA, LDA, iLDA and FiLDA. Then, KNN was applied to classify the test samples. We evidently discovered that the classification accuracies of red jujube varieties were different when different feature extraction algorithms were used in the experiments in The number of training samples and test samples was changed, but other experimental conditions were consistent. To classify red jujube varieties quickly, nondestructively, and effectively, FiLDA algorithm coupled with NIR spectroscopy was proposed in this study. FiLDA algorithm is the derivation of fuzzy set theory and iLDA. FiLDA is a new fuzzy feature extraction algorithm that combines the fuzzy algorithm with the iLDA, and it is applied in the identification of red jujube varieties. The NIR spectral data were collected for 300 red jujube samples of 5 types by using the NIR-M-R2 spectrometer. NIR spectra were processed by S-G filter, PCA, LDA, iLDA and FiLDA, respectively. Finally, KNN was employed as a classifier to recognize the red jujube varieties. FiLDA was able to identify red jujube samples accurately and had the highest classification accuracies than other feature extraction algorithms. In addition, NIR spectroscopy has been widely used in the field of food inspection, and in the food supply chain. The experimental results proved that FiLDA algorithm coupled with NIR spectroscopy could play an important role in the classification of red jujube varieties.


RK and LK DNAmAge are older than blood DNAmAge  and RK and LK AgeAcc present higher score (this mean the AgeAcc is faster) than that of blood leukocytes (p = 0.0271 and p = 0.0245) in the same donor. TL of RK and LK are instead longer than that of blood (p = 0.0011 and p = 0.0098) and the increase in Remuzzi-Karpinski score is strongly correlated with kidney TL attrition (p = 0.0046). Finally, blood and kidney TL (p < 0.01) and DNAmAge (p < 0.001) were correlated. These markers can be evaluated in further studies as indicators of biological age of donor organ quality and increase the usage of organs from donors of advanced age therefore offering a potential translational research inkidney transplantation.The biological age of an organ may represent a valuable tool for assessing its quality, especially in the elder. We examined the biological age of the kidneys [right (RK) and left kidney (LK)] and blood leukocytes in the same subject and compared these to assess whether blood mirrors kidney biological aging. Biological age was studied in  Organ failure represents a dramatic socio-economical burden worldwide which prevalence is likely to increases sharply with population aging. The ideal therapeutic solution is represented by the transplantation of an allogeneic equivalent obtained by a human donor. However, there is a dramatic mismatch between the number of patients in transplantation list and the effective availability of donor's organs . StrategWithin the context of kidney transplantation in which organ shortage remains a problem, donor's age is however one of the main factors influencing the decision of accepting the kidneys , 2. KidnAlthough the chronologicalage of the donor can influence the quality of the kidney to be transplanted, it may not be a reliable indicator of the rate of physiological breakdown of the body or of the organs, as people do not age at the same rate. Genetic and environmental factors can impact on biological aging, causing different aging trajectories and health outcomes in each person –8. In adThe biological age is not that indicated on the identity card but is written on the DNA. Growing indications have shown that telomere length (TL) and age-correlated DNA methylation changes in certain CpG loci (DNAmAge) are early hallmarks of biological aging, and may be primary indicators of cellular dysfunction and in age-related disorders , 10. TL,Studies comparing biological age indicators measured in different tissues of the same subject are however in most of cases on TL measures made on cadavers, donors elderly patients, and the measurements seem correlated –23. TherFurthermore, the biological age of an organ may then represent a valuable tool for the assessment of its quality, as it could correlate more closely to its functional reserve, and predict the transplantation outcome more accurately than the present evaluation methods.The aim of our study was:1) To determine the biological age of the kidneys by measuring the mitotic (TL) and the non-mitotic epigenetic age (DNAmAge) of renal cells collected from kidney samples and to compare it with the Remuzzi score with the purpose of defining a biomarker for organ quality assessment.2) To compare the DNAmAge of peripheral blood leukocytes and kidneys, in order to establish whether blood may be an accurate indicator of kidney biological age.Over a time span of 22 months (from March 2019 to January 2021) renal true-cut biopsies and blood samples were obtained in the same time from 36 deceased kidney donors for whom the procurement was performed by the surgical team of Kidney and Pancreas Transplantation Unit - Department of Surgical, Oncological and Gastroenterological Sciences, University Hospital of Padua. The donors included in the study were those for whom a renal biopsy was deemed clinically indicated either for the assessment of chronic damage (Blood samples (3–4 ml) from the donors were collected in K3EDTA and PAXgene tubes . The tru-cut biopsies were placed in all protected tissue reagent-RNA Later  for DNA/RNA stabilization. All collected samples were then, transferred to our laboratory of Genomic and Environmental Mutagenesis  for genetic and epigenetic analyses and stored at −20°C, until analyses were performed. Our Local Ethical Committee, which is named the Ethical Committee for Clinical Trials of the Province of Padova, approved the study (protocol number 2246P) in accordance with principles of the Helsinki Declaration, allowing a waiver from consent. All methods were carried out in accordance with relevant guidelines and regulations.We collected data on the following donor characteristics: age, gender, smoking, comorbidities, cause of death, blood parameters and renal function. We also recorded the histological Remuzzi-Karpinski score of the kidneys when available for clinical necessity as for the Nord Italian Transplant programm (NITp) algorithm for allocation to single or dual transplantation .DNA extraction was performed on all samples of whole blood and renal biopsies using an automated QIAcube System according to the DNAeasy Blood and Tissue kit procedure  as previously described . DetailsDNAmAge was assessed by analyzing the methylation levels of five selected markers in genomic DNA using bisulfite conversion and Pyrosequencing methodology as previously described , 10, 17.AgeAcc was assessed for both renal tissue and blood leukocytes of each donor. AgeAcc was estimated as the difference between the DNAmAge and the chronological age of the donors.TL was measured in genomic DNA by quantitative Real-Time PCR by estimating the ratio of telomere repeat copy number (T) to single nuclear copy gene (S) in experimental DNA samples relative to the T/S ratio of a reference pooled sample as previously reported –27. The n = 15 (power 0.9).Estimating that a significant correlation would be in the order of r = 0.80, we calculated that the sample to obtain statistical significance (α 0.01) should be T-test, while comparison between all samples in the two groups was also made using Mann-Whitney U Test. Correlation was evaluated by simple linear regression models  in order to provide a measure of the strength of dependence between two variables. Results were considered significant when a p value of < 0.05 was obtained.Statistical analyses were performed with StatsDirect software. Data are expressed as median, minimum and maximum values unless otherwise specified. Values of TL, DNAmAge and AgeAcc in Kidneys  and blood, of the same patient, were compared by (two-tailed) paired n = 27 paired RK vs blood DNAmAge donors (B), paired t-test: median 69 years vs. median 65 years; p = 0.0271) and left kidney (LK) (n = 27 paired LK vs blood DNAmAge donors (C), paired t-test: median 69 years vs. median 65 years; p = 0.0245) are significantly older than blood leukocytes DNAmAge. RK and LK DNAmAge are similar (A).In n = 27 RK vs blood AgeAcc donors (E), paired t-test: median−5 years vs. median−8 years; p = 0.0271, and n = 27 LK vs. blood AgeAcc donors (F), paired t-test: median−6 years vs. median−7 years; p = 0.0245). No difference between RK and LK AgeAcc is observed (D).Still in n = 27 paired t-test: RK TL vs. blood donors (B), median 1.18 T/S vs. median 1.15 T/S; p = 0.0011; n = 27 LK TL vs. blood donors (C), paired t-test: median 1.25 T/S vs. median 1.15 T/S; p = 0.0098). No difference between RK and LK TL is observed (A).p = 0.0046). Remuzzi-Karpinski score and DNAmAge were instead positive weakly correlated (p = 0.085). In p = 0.0173), but not age, gender and DNAmAge.In p = 0.0003; LK = −0.638, p < 0.0001; blood leukocytes = −0.526, p < 0.0001).Simple linear regression analyses show that AgeAcc of RK, LK and blood leukocytes are negative correlated with chronological age in p < 0.0001 in p = 0.0532; LK = −0.403, p = 0.0011; blood leukocytes = −0.277, p = 0.0224).DNAmAge of RK, LK and blood leukocytes are positive highly correlated with chronological age  of RK, LK and blood leukocytes are negatively associated  were associated with age-adjusted DNAmAge . These positive and significant correlations are reported in 3/mL), smoking and chronic diseases including arterial hypertension, diabetes and cancer on blood leukocytes DNAmAge, AgeAcc and TL, shows that the main determinants are chronological age for DNAmAge (p < 0.0001) and arterial hypertension for TL (p = 0.0014).Multiple regression analysis  of the ip < 0.0001) and kidneys TL (p = 0.0011).Multiple linear regression analysis  of the iIn this study, we have determined the biological age of the kidney and of peripheral blood leukocytes of donors, by measuring the non-mitotic epigenetic age (DNAmAge and AgeAcc) and the mitotic age (TL) and correlate it to the Remuzzi-Karpinski score.The main findings stemming from this work reveal that:a) The non-mitotic epigenetic age (DNAmAge and AgeAcc) of both kidney tissues (RK and LK) is older than that of blood leukocytes;b) AgeAcc of both kidney tissues (RK and LK) and blood leukocytes significantly slow down with advancing in chronological age;c) The mitotic age (TL) of both kidney tissues (RK and LK) is younger than that of blood leukocytes and TL attrition is strongly correlated with the increase in Remuzzi-Karpinski score;d) DNAmAge, and TL of RK and LK highly correlate with those of blood leukocytes.in vivo regeneration. In our previous studies, we demonstrated that intensive relaxing training turns back the epigenetic clock , together with improvement in clinical blood parameters  and with a clinical regaining of endothelial function, in patients after myocardial infarction, and even more in healthy subjects  to 12 score  . An incrIn order to promptly translating our work into the clinical practice, we also assessed the similarity level of biological ages between kidneys and blood leukocytes in the same donor. We observed a robust correlation between DNAmAge and TL of kidneys (RK and LK) and blood leukocytes, suggesting that the latter could be a surrogate tissue of the kidney status for biological aging studies. To the best of our knowledge, such correlation for DNAmAge has not been investigated before now. Determining the biological age of blood and estimating its correlation with that of the kidneys is of paramount importance to identify and set up a simple and reliable tool for screening potential donors, in particular for accepting the kidneys for transplantation from elderly donors. In a real clinical scenario, at the donor hospital site, blood samples may be easily and quickly acquired and sent to the laboratory for biological age analysis. Further studies are hence needed to optimize the use of blood as a surrogate indicator of kidney's biological age in clinical practice.Furthermore, the slowing down of biological aging (AgeAcc) in older donors could be a key parameter in the evaluation and use of organs from these donors. For example, we can hypothesize to define a cutoff of AgeAcc, beyond which the donor becomes at risk of graft dysfunction rather than considering the value of the chronological age.Our study for the first time evaluated the non-mitotic epigenetic age and the mitotic age from kidneys of donors by comparing it with that of their blood leukocytes in healthy donors. This pioneering aspect certainly represents one of the main strengths of our study. Analyzing DNAmAge and TL by using an almost totally automated workflow, which allows us to perform the analyses in a standardized way reducing errors, is another strong point of this study. Furthermore, no significant difference was found in the distribution of RK and LK DNAmAge, and in TL as well. Our study for the first time evaluates the non-mitotic epigenetic age (DNAmAge) and mitotic age (TL) of donor kidneys, and levels were similar for both kidneys. This suggests that, in the future, biological age analysis can be performed either in the RK or LK. Lastly, our results showed that kidneys TL and DNAmAge correlate with those of blood leukocytes, suggesting that blood could be a more easily and quickly acquired surrogate tissue of the kidney for biological aging studies for translating into the clinical practice.A limitation of our study could be the small number of subjects enrolled and number of samples collected, which was due to the limited available donors on which biopsies can be performed due to clinical reasons. However, samples analyzed are adequate from the statistical point of view. Another limitation could be that renal biopsy, from which we extracted DNA for biological age analysis, contains different cell types. However, up to now, renal biopsy remains the gold standard by which essential diagnostic and prognostic information is obtained in kidney transplantation. Biopsy methodologies have been developed to assess the acceptability of an organ before transplantation and to assess and predict renal allograft performance after implantation , 5. In an = 420) and then they validated it in a smaller one (n = 300), covering the entire adult life span. Furthermore, to increase the practicability of these tests, and used the locus-specific technology pyrosequencing which having the potential for multiplexing, makes the technical analysis achievable in few hours and reduce the cost of technical analysis, methods with only few loci were taken into account. Furthermore, we have automated to increase the efficiency and rapidity, maintaining high prediction accuracy . LF, FN, MB, PR, and EN: provided the samples. MC: performed the samples' analysis. SP and MC: analyzed the data. SP, MC, and FN: wrote the paper. All authors contributed to the article and approved the submitted version.This study was supported by the funding Grants the L.I.F.E.L.A.B., Consorzio Per La Ricerca Sanitaria-CORIS (Veneto Region).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Maintaining the emotional well-being of learners during a pandemic is important. This study explored the effects of two emotion regulation strategies  and perceived control on full remote learners' anxiety during Covid-19, and their relationship to perceived learning. Structural equation modeling was used to analyze 239 questionnaires completed by Chinese graduate students taking a course remotely from home for 13 weeks. This study showed that reappraisal was positively related to perceived control, whereas suppression was negatively related to perceived control. Reappraisers perceived more learning, whereas suppressors experienced more anxiety. Anxiety was significantly and negatively related to perceived learning. Mediation analyses showed the existence of different patterns of mediation in the pathways from the two types of emotion regulation to perceived learning. These findings are discussed in relation to relevant studies conducted during non-pandemic periods and Covid-19, and based on the results we highlight the need for interventions aimed at developing adaptive emotion regulation strategies and reducing anxiety in emergency remote learning. On March 11, 2020, the World Health Organization (WHO) announced Covid-19 (coronavirus disease) as a pandemic  and response-focused strategies  , perceived control, anxiety as an achievement emotion, and perceived learning during Covid-19 remote learning. Perceived learning is indicative of student achievement  and arousal (low-high intensity). In terms of object focus  emotions by intervening in specific stages of the emotion production system using conscious and non-conscious strategies Gross, . Dependirecontrual  and repurposing   and expressive suppression (a response-modulation strategy). These two strategies have been studied most frequently compared to other emotion regulation strategies. Reappraisal regulates an emotional impact by changing the way events are evaluated, and operates primarily through meaning-evaluation mechanisms Gross, , 2001. IAccording to the appraisal model that aims to unify appraisal, emotion regulation, and emotion generation , which deserves academic attention in the context of Covid-19 full remote learning, has not been explored so far. The present study sought to fill this gap by examining how reappraisal and suppression are related to remote learners' perceived control, anxiety and perceived learning. Based on the literature reviewed, we propose the following model and hypotheses . In addiH1: Cognitive reappraisal is positively related perceived control (H1a) and perceived learning (H1c), but negatively related to anxiety (H1b).H2: Expressive suppression is negatively related to perceived control (H2a) and perceived learning (H2c), but positively related to anxiety (H2b).H3: Perceived control is negatively related to anxiety (H3a), but positively related to perceived learning (H3b).H4: Anxiety is negatively related to perceived learning.H5: Cognitive reappraisal indirectly affects perceived learning through perceived control and anxiety.H6: Expressive suppression indirectly affects perceived learning through perceived control and anxiety.http://www.moe.gov.cn/jyb_xwfb/gzdt_gzdt/s5987/202001/t20200129_416993.html), which required students at all educational levels to take courses at home. Using a convenience sample, this study investigated a group of graduate students' perceptions of a full remote course on academic writing and research methods. They were enrolled in a medium-sized public university in southwest China. Prior to the Covid-19 outbreak, this course was routinely taught face-to-face in brick-and-mortar classrooms. During the pandemic outbreak, students took the first 13 weeks of the 18-week course (late February to late May) remotely at home, and most of them returned to university to take the course face-to-face in the 14th week.On 29 January, 2020, due to the outbreak of Covid-19, the Ministry of Education of the People's Republic of China issued a policy of “suspending classes without stopping learning” . The course was mainly taught online (synchronously webcasted by lecturers) using Tencent Classroom , and also included synchronous and asynchronous classroom and group discussions, as well as online question and answer sessions. The course was assessed based on assignments, online class participation, and a course paper submitted at the end of the semester.In week 13, an invitation with a link to the questionnaire was sent out via the course lecturers to invite their students to participate in this study. The introduction page of the questionnaire described the nature of this study, gave consent forms, and informed each student that his participation was completely voluntary and his response would be kept confidential. The survey was hosted on Wenjuanxing . It should be pointed out that ethics approval was not required at the time this study was conducted as per the local legislation and institutional requirements. However, informed consent was obtained from all participants.Mean = 23.74; SD = 1.22), and 32% of them were male and 68% were female. They originated from different provinces and each studied at home during the time the present study was conducted. They majored in economics, business management, finance, and accounting.Initially, we received a total of 272 questionnaires (response rate: 84%). Prior to the main survey, a pilot study was conducted with 15 graduate students. We removed questionnaires that were completed within 100 s based on the researchers' evaluation of the pilot study and the average time to complete the questionnaire in the main survey. In addition, we removed questionnaires completed by selecting the same option for all or the majority of the scaled measurement items, including the reversed ones. According to the above criteria, 239 valid questionnaires were entered into the analysis. Participants were between 21 and 30 years of age , ex-ante approaches were adopted in the design of questionnaires  to 5 (strongly agree). Reappraisal scale consists of six items , and suppression scale consists of four items . The Chinese translations of these items were adopted from Chen et al.  designed by Perry et al. (strongly disagree to 5 = strongly agree). The PACS has been used in examining online learning  developed by Perry et al. . AEQ was used to examine the emotions of online learners in previous studies Perceived Learning Scale designed by Rovai et al. .Perceived learning was measured using the i et al. . The scaTo ensure the validity of the translation of CAP Scale, a back-translation procedure was used Brislin, . First, The participants were asked to report gender and age. Gender and age were used as covariates in the present study, as evidence indicates that emotion varies with gender and age in educational contexts , the comparative fit index (CFI), the Tucker-Lewis index (TLI), the root mean square error of approximation (RMSEA), and the standardized root mean square residuals (SRMR). For CFI and TLI, a value >0.95/0.90 indicates a good/adequate model fit. For RMSEA, a value ≤ 0.06/0.08 indicates a good/adequate model fit, and for SRMR, a value ≤ 0.08/0.10 indicates a good/ adequate model fit.Statistical analyses were performed using SPSS v.25 and SPSS Amos v.24. We followed a two-stage approach suggested by Anderson and Gerbing  to analyFinally, a serial mediation analysis was performed using Preacher and Hayes  method. The reliability of the five constructs were measured by Cronbach's Alpha and composite reliability. As shown in 2 (454) = 536.076, p < 0.05, CFI = 0.969, TLI = 0.966, RMSEA = 0.028, SRMR = 0.050.The construct validity was measured using CFA. Standardized factor loadings and goodness of fit indexes of each construct are reported in Discriminant validity was checked using heterotrait-monotrait ratio of correlations (HTMT)  and perceived learning , but negatively associated with anxiety . Suppression was negatively correlated with perceived control  and perceived learning , but positively associated with anxiety (r = 0.37 p < 0.001). In addition, perceived control was negatively correlated with anxiety , and anxiety was negatively associated with perceived learning .The results of the bivariate correlations are generally in line with our expectations. Reappraisal was positively associated with perceived control (2 (512) = 595.261, p < 0.05, CFI = 0.968, TLI = 0.965, RMSEA = 0.026, SRMR = 0.049. The model explained a large proportion of variance in perceived control (R2 = 0.29), anxiety (R2 = 0.32), and perceived learning (R2 = 0.56). The structural model with standardized coefficients is presented in The indices showed that the data fitted the structural model: χp < 0.001) and perceived learning . H1b posits that reappraisal is significantly and negatively related to anxiety. This hypothesis was not supported (p > 0.05). As to H2a and H2b, as anticipated, suppression was negatively related to perceived control , but positively related to anxiety . Suppression was not significantly related to perceived learning; thus, H2c was not supported (p > 0.05). Regarding H3a-b, perceived control was negatively related to anxiety , but positively related to perceived learning ; thus, both hypotheses were supported. H4 posits that anxiety is negatively related to perceived learning, and this hypothesis was supported .Regarding H1a and H1c, as expected, cognitive reappraisal was positively related to perceived control , and accounted for 57.1% of the association.In the suppression-learning association, the indirect effect of perceived control alone  and that of anxiety alone  were both found to be significant. A significant serial mediation effect through both control and anxiety was also found . Thus, we found support for H6.The percent of suppression-learning association mediated was 47.8% through perceived control alone, 33.2% through anxiety alone, and 7.5% through the path including both control and anxiety. The results suggested that suppression affected perceived learning mainly through perceived control alone and through anxiety alone. Moreover, the indirect effect of perceived control in the suppression-anxiety association was found to be significant , and explained 18.7% of the association.The purpose of this study was to investigate the impact of emotion regulation strategies on control appraisal and anxiety among remote learners in the context of a global health crisis, and thus to identify the mechanisms by which anxiety arises. Students who attended the course remotely from home completed a questionnaire related to the measures of the studied variables. As expected, reappraisers perceived higher control with higher learning, whereas suppressors had lower perceived control and higher learning anxiety. Students with high perceived control experienced less anxiety and higher perceived learning. Higher anxiety was associated with lower learning. The paths of reappraisal to anxiety and suppression to perceived learning in the model were not as significant as expected. We explored the possible mediation effects of perceived control and anxiety, and all indirect effects in the association between emotion regulation and perceived learning were found to be significant, except for the indirect effect of anxiety alone in the reappraisal-learning association. According to the magnitude of mediations, perceived control was a particularly important mediator in the reappraisal-learning association, and both perceived control and anxiety were important mediators in the suppression-learning association.A key proposition of the appraisal model (Yih et al., As predicted by Pekrun's  control-stress-is-enhancing mindset, flexibly viewing stress as an opportunity for growth (Hagger et al., broadening and building theory (Fredrickson, Consistent with previous literature (Jamieson et al., Chronic attempts to avoid an unwanted thought can lead to an increase in the frequency, severity, and accessibility of that thought (Wegner et al., Similar to Low et al.'s  study 2 attentional control theory (Eysenck et al., According to the This study has several limitations that we would like to highlight. First, the results of a study based on a convenience sample may limit its generalizability or external validity. Our study was conducted on a full remote course taken by graduate students at a university in China during Covid-19. Because of the differences in the specific implementation of emergency remote teaching across countries and grade levels (Hall et al., Despite these limitations, this study provides some insight into teaching and learning during emergencies. These findings highlight the need for interventions to reduce remote learners' anxiety. Training in emotion regulation has been shown to be effective in improving the ability to cope with various emotions and reducing anxiety (De Witte et al., Finally, the implications of this study for future research are as follows. According to the process model of emotion regulation Gross, , regulatThis study examined the effects of two emotion regulation strategies on perceived control over learning and anxiety in a sample of graduate students taking a remote course during the pandemic. The results showed that cognitive reappraisal was positively related to perceived control and perceived learning. Expressive suppression was negatively related to perceived control, but positively related to anxiety. Anxiety was significantly, negatively related to perceived learning. We found the existence of different patterns of mediation in the pathways from the two types of emotion regulation to perceived learning. These results were interpreted in the light of the model that aims to unify emotion regulation and perceived control, the control-value theory and the attentional control theory. For learners in emergency remote learning situations, rather than holding emotions inside, understanding and accepting emotions and allowing them to be regulated using cognitive reappraisal can promote control over a situation, healthy emotional development, and learning outcomes.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study.TZ: conceptualization, methodology, data analysis, and writing. ZF and XL: conceptualization, writing, and editing. LY: data analysis, writing, and editing. WH: methodology. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Previous studies suggested that dietary inflammatory index (DII) was associated with a variety of adverse health conditions. However, less is known about the role of DII in prediabetes and insulin resistance (IR). Therefore, this study aimed to investigate whether DII is associated with prediabetes and IR in American adults.β: 0.009; 95%CI: 0.005 to 0.012), fasting serum insulin (FSI)  and homeostatic model assessment of insulin resistance (HOMA-IR) . Participants in the highest tertile of DII score have increased odds of prediabetes  and IR  compared with those in the first tertile of DII score.DII scores were calculated using the average of two 24-hour dietary recalls. Linear regression models were performed to evaluate the associations of DII with markers of Type 2 diabetes (T2D) risk, and the associations of DII with prediabetes and IR were estimated using logistic regression model. The diet of the participants showed an anti-inflammatory potential, with a mean DII score of −0.14 (range: −5.83 to +5.32). After controlling for multiple potential confounders, DII scores were positively associated with fasting plasma glucose (FPG) (This study indicates that DII was positively associated with FPG, FSI, and HOMA-IR, and a more pro-inflammatory diet was related to increased odds of insulin resistant and prediabetes. Currently, there are about 34.2 million people with diabetes in the US, and the prevalence of diabetes is expected to continue to rise in the future . Type 2 Prediabetes and insulin resistance (IR), major contributing factors in the development of T2D, were characterized by abnormal glucose metabolism , 3, 4. TThus, the main objective of present study was to investigate the associations of the DII with IR and prediabetes in a national representative population in America. The second aim of this study was to investigate the associations between DII and the markers of T2D risk, namely, fasting plasma glucose [FPG], glycohemoglobin [HbA1c], fasting serum insulin [FSI], and homeostatic model assessment of insulin resistance index [HOMA-IR].http://www.cdc.gov/nchs/nhanes.htm).The data of current study were extracted from 2007 to 2016 cycles of the National Health and Nutrition Examination Surveys (NHANES), which are ongoing, stratified, multistage probability surveys of the non-institutionalized civilian population residing in the 50 states and districts of Columbia in the United States. The survey consists of questionnaires administered in the home, followed by a standardized health examination in specially equipped mobile examination centers. Beginning in 1999, most data in this nationally representative survey have been released online in 2-year cycles. The NHANES procedures were approved by the National Center for Health Statistics research ethics review board, and the informed consent was obtained from all participants prior to their inclusion in the surveys. The official website provides more detailed information on the methods and protocols of the NHANES  pregnant women (n = 307); b) participants with known diabetes ; c) those with missing data on FPG, HbA1c, and FSI ; d) those with attending the morning examination after fasting <8 h (n = 748); e) those whose dietary recall status is unreliable or does not meet the minimum criteria ; then, 8,727 remained in the study. After further excluding those with missing data on key covariates including sex, educational attainment, race/ethnicity, body mass index (BMI), family poverty income ratio (PIR), hypertension, serum cotinine, and physical activity (n = 801), finally, a total of 7,926 participants  were enrolled in the present study. The results of comparisons among the included participants and those adults without missing data on T2D risk markers and all participants are shown in The development and validation of the DII has previously been reported elsewhere , 20. BriIn this study, dietary data used to calculate the DII score was evaluated by the average of two 24-h dietary recalls. In brief, through face-to-face interview  and telephone interview , individual foods/beverage consumed during a 24-hour time period before the interview was obtained. The United States Department of Agriculture Food and Nutrient Database for Dietary Studies was used to quantify specific nutrients in the reported dietary components . In the FPG was measured by an enzyme hexokinase method. FSI was measured using an immunoassay method. HbA1c from whole blood was measured using the boronate affinity high performance liquid chromatography system. The concentrations of FPG, FSI, and HbA1c were adjusted for differences in laboratory methodology in the NHANES 2007–2016. The IR status was measured by HOMA-IR, and the 75th percentile value of HOMA-IR was used as a cut-off level to define the IR in present study . The cor2)  . PIR wasCategorical variables were expressed as counts (percentages) and were compared using the chi-squared test. Continuous variables were expressed as mean  if data presented a normal distribution and were compared using analysis of variance (ANOVA), or expressed as medians (25th–75th) if data presented a skewed distribution and were compared by the Wilcoxon rank sum test. FPG, FSI, HbA1c, and HOMA-IR were log-transformed to better approximate a normal distribution. The associations of DII with FPG, FSI, HbA1c, and HOMA-IR were estimated using linear regression model, and the associations of DII with IR and prediabetes were estimated using logistic regression model. Three models were applied in the present study, with adjustment for potential confounders ascertained based on prior publications –31 Model2 for the present study. Thus, the present study subjects were classified into two subgroups . As an interaction term, DII × Obesity, was inserted in the regression models to obtain P-value for interaction. In addition, the restricted cubic spline models were applied to evaluate the dose–response relationships of DII with prediabetes and IR in all the participants and subgroups, with adjustment for abovementioned covariates.Since previous studies have reported significant associations of obesity with prediabetes and IR , 33, a sTo evaluate the robustness of the associations of DII with IR and prediabetes, we further performed a sensitive analysis with adjustment for white blood cell count to control the circulating level of inflammatory marker. Additionally, we performed another sensitive analysis with strict criteria to define prediabetes (HbA1c (6.0–6.5%) and/or FPG (110–125 mg/dl)). Lastly, because there were participants with undiagnosed diabetes in the present study, we also performed an analysis to investigate the association between DII and undiagnosed diabetes.Survey weighing procedures accounted for the effects of stratification and clustering used in the NHANES study design. We constructed fasting subsample weights for analysis as appropriate to obtain US nationally representative estimates. All data cleaning and statistical analyses were performed using R software (version 3.6.3) .β coefficients (95% CI) for the highest tertile of DII score were 0.021 (95%CI: 0.013 to 0.028), 0.191 (95%CI: 0.153 to 0.229), and 0.212 (95%CI: 0.172 to 0.252) for FPG, FSI, and HOMA-IR, respectively.P for trend <0.001). In the results of subgroup analyses, the association between DII and prediabetes was more evident among participants with obesity , but there was no significant modification effect of BMI on the DII-prediabetes association .The relationship between DII and prediabetes according to the tertiles of DII score is listed in P-value for interaction = 0.653).The association between DII and IR according to the tertiles of DII score is listed in P for non-linearity = 0.112) and prediabetes (P for non-linearity = 0.342), but a significant non-linear association of DII with IR was observed in the participants without obesity , IR, and prediabetes, suggesting an important role of diet on the homeostasis of glucose metabolism. Compared with previous studies, findings from the present study differed from several earlier studies , 19, 41,Biologic mechanisms underlying the associations of DII with prediabetes and IR remain unclear. Nonetheless, previous studies suggested that pro-inflammatory diet could promote low-grade inflammation  that is The present study was based on a large nationally representative survey, which allowed to adjust for multiple covariates and increased the statistical power of the findings. Despite its strengths, we also acknowledge that this study was subject to some limitations. First, the temporal or causal relationships cannot be inferred because of the cross-sectional design for NHANES. However, the study participants were free from known diabetes, so they would not change their diet due to the diagnosis, and thus the dietary information collected at the same time when blood samples were collected could reflect participants’ usual dietary habits. Second, although multicovariates were included in models, we could not exclude the residual confounding effect from unmeasured or unavailable covariates . Third, only 31 out of 45 parameters were extracted from 24-hour recalls due to the questionnaire setting. However, previous studies have shown that there was no degradation in predictive ability of the DII in calculation using only 27 or 28 parameters , 55. FouIn conclusion, the present study suggests that DII was positively associated with FPG, FSI, and HOMA-IR, and a more pro-inflammatory diet (expressed as a higher DII score) may increase the odds of insulin resistant and prediabetes. Therefore, the promotion of anti-inflammatory diet might maintain glucose–insulin homeostasis, and subsequently lower the odds of insulin resistant and prediabetes.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the National Center for Health Statistics research ethics review board. The patients/participants provided their written informed consent to participate in this study.YS, XW, JW, XM, HL, and YX conceived and designed the research. YS wrote the manuscript draft. YS performed the statistical analysis. YS, XW, JW, and XM participated in revising the manuscript. HL and YX provided content and feedback to the manuscript, reviewed and edited. All authors contributed to the article and approved the submitted version.This research was funded by the Guangdong Science & Technology Development Project [2013B031800012], and the National Natural Science Foundation of China [81874260].The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.The reviewer YBZ declared a shared affiliation with several of the authors, YS, XM, YX, to the handling editor at time of review.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


These components act on key target genes such as AKT1, IL6, MAPK3, TP53, EGFR, SRC, and TNF and regulate the PI3K/Akt-signaling and MAPK-signaling pathways. These molecules participate in a series of processes such as cellular differentiation, apoptosis, metabolism, and inflammation and can ultimately be used to treat PMOP; they reflect the overall regulation, network regulation, and protein interactions.Deer velvet antlers are the young horns of male deer that are not ossified and densely overgrown. Velvet antler and its preparations have been widely used in the treatment of postmenopausal osteoporosis (PMOP) in recent years, although its mechanism of action in the human body remains unclear. To screen the effective ingredients and targets of velvet antler in the treatment of PMOP using network pharmacology and to explore the potential mechanisms of velvet antler action in such treatments, we screened the active ingredients and targets of velvet antler in the BATMAN-TCM database. We also screened the relevant targets of PMOP in the GeneCards and OMIM databases and then compared the targets at the intersection of both velvet antler and PMOP. We used Cytoscape 3.7.2 software to construct a network diagram of “disease-drug-components-targets” and a protein-protein interaction (PPI) network through the STRING database and screened out the core targets; the R language was then used to analyze the shared targets between antler and PMOP for GO-enrichment analysis and KEGG pathway-annotation analysis. Furthermore, we used the professional software Maestro 11.1 to verify the predictive analysis based on network pharmacology. Hematoxylin-eosin (H&E) staining and micro-CT were used to observe the changes in trabecular bone tissue, further confirming the results of network pharmacological analysis. The potentially effective components of velvet antler principally include 17 Postmenopausal osteoporosis (PMOP) refers to a metabolic disease in which the endocrine function of women's ovaries declines after menopause and the levels of estrogen diminish, which in turn causes bone resorption by osteoclasts to exceed bone formation by osteoblasts –3. PMOP Deer antler was included in the 2020 Chinese Pharmacopoeia , and itsNetwork pharmacology involves biology, biological network construction and analysis, connectivity, redundancy, and pleiotropy. It is used to reveal the effectiveness, toxicity, and metabolic properties of drugs. Network pharmacology transcends the traditional drug research and development model dominated by “one drug, one target, and one disease” and opens a new research model of the complex network relationship among multiple targets and multiple diseases. Velvet antler and its preparations have been widely used in the treatment of PMOP in recent years, but its underlying mechanism of action in the human body is still unclear. Therefore, in the present study, we used network pharmacology to screen the primary active ingredients and key targets of velvet antler treatment for PMOP and explored the mechanism of action of velvet antler in a “multicomponent, multitarget, and multipathway” manner.We herein screened the active ingredients and targets of velvet antler in the BATMAN-TCM database. We also screened the relevant targets of PMOP in the GeneCards and OMIM databases and then compared the targets between velvet antler and PMOP. The target points of osteoporosis were then taken as an intersection. We used Cytoscape 3.7.2 software to draw the network diagram of “disease-drug-component-target.” We constructed a protein-protein interaction network (PPI) through the STRING database and screened out core targets. The R programming language was adopted to perform GO-enrichment analysis and KEGG pathway-annotation analysis on common targets of velvet antler and PMOP. Eleven core targets were obtained from the PPI network for molecular docking analysis. We then utilized the experimental results to develop our conclusions.p < 0.05. Thus, the active ingredients contained in deer antler and their corresponding potential targets were screened.In the BATMAN-TCM, a bioinformatics analysis tool platform for elucidating the molecular mechanisms underlying traditional Chinese medicine, “deer antler” was selected as the keyword and “drug-target” as the screening condition, with the similarity model threshold score cut-off ≥20 and In the GeneCards and OMIM databases, “postmenopausal osteoporosis” was used as the search term for all gene targets related to PMOP and then the intersection of the selected PMOP targets and the potential targets of deer antler were assessed, that is, the potential targets of velvet antler in the treatment of PMOP.The intersection target data for PMOP and velvet antler were input into Cytoscape 3.7.2 software to construct the regulatory network “disease-drug-component-target.” The different network nodes, respectively, represented PMOP, the traditional Chinese medicine velvet antler, the effective components of velvet antler, and the common targets of PMOP and velvet antler; the connecting line between the nodes represented the mutual relationships and effects.http://string-db.org) and the screening condition was set—species “Homo sapiens”—with the remaining conditions set as defaults; thus, the PPI network for velvet antler in the treatment of PMOP was constructed. The Cytoscape 3.7.2 software plug-in network analyzer was used to analyze the topological parameters of the average and maximal degrees of freedom in the PPI network. The core targets were screened out based on the metric value. Those with more chance to be the core ones of the treatment had larger value. The upper limit of the screening range was the maximum degree value in topological data, and the lower limit was twice the average degree of freedom [The common targets of PMOP and velvet antler were input in the STRING database . The filtrate was freeze-dried by a Heto PowerDry LL3000 Freeze Dryer  and stored at −80°C. When the mice need to be administered by gavage, the velvet antler was dissolved in pure water. FA1004N electronic balance , Leica RM2255 paraffin microtome , Leica EG1140 paraffin-embedding machine , Olympus BX51 optical microscope , and NIS-ELEMNT BR image analysis system (Japan NIKON Company) were used.The deer antler used in the following experiments was the same as the ones prepared as previously described . Antler Eight-week-old C57 female mice were purchased from Liaoning Changsheng Biotechnology Co., Ltd.  2020-0001). After 1 week of adaptive feeding, a dorsal approach was used to remove both ovaries. Models were created and randomly allocated to the control group and the administration group. All mice were intraperitoneally injected with penicillin sodium  for three consecutive days after the operation and were bred adaptively for one week. The control group was administered pure water intragastrically (i.g.), and the administration group was administered 4 mg/10 g/d deer antler i.g. for three consecutive weeks. After the experiment, the mouse femurs were removed under anesthesia. All experimental procedures were carried out in accordance with national and international guidelines and regulations, and all experiments were approved by the Animal Ethics Committee of the Changchun University of Traditional Chinese Medicine (no. ccucm-2017-0015).μA, and a 14 min scanning time [The femur from each animal was sampled and the soft tissue was cleaned off. The microarchitecture of the femur was analyzed using a Quantum GX Micro-CT imaging system . Each sample was carefully positioned such that the orientation of the femoral shaft was as vertical as possible. The distal femur was scanned with the following settings: 90 kV, 80 ing time . Bone moing time .μm thick slices that were stained with hematoxylin and eosin (H&E). Section images were acquired with an Olympus BX51 optical microscope . The distribution of trabecular bone was observed. The static parameters, namely, osteoblast surface/bone surface (ObS/BS), osteoclast surface/bone surface (OcS/BS), eroded surface/bone surface (ES/BS), and osteoid volume/bone volume (OV/BV), were analyzed with a quantitative stereological method for histology known as the Weibel technique [The femoral samples were fixed in 4% paraformaldehyde for 48 h, followed by decalcification in ethylenediaminetetraacetic acid (EDTA), dehydration in alcohol, clearing in xylene, and finally embedding in paraffin for further tissue sections. A paraffin microtome  was used to section the sample into 4 echnique . The staechnique .t-test  and expressed as the mean ± SD.The Shapiro–Wilk normality test was used to determine the distribution of the data as the sample size was less than 100. All of the groups were found to be normally distributed. Thus, the data were analyzed by SPSS 25.0 software using parametric Student's p < 0.05 with strict screening, a total of 14 potential velvet antler active molecules were retrieved. The effective chemical components, as presented in β-estradiol, glucosamine, adenosine triphosphate, and oestrone.In BATMAN-TCM, with “antler” as the keyword, the screening condition set to “drug-target,” the similarity model threshold score cut-off set to ≥20, and As shown in β-D-glucosyl gentiopicroside), reflecting the multicomponent and multitarget effects of velvet antler on PMOP. As shown in β-estradiol, oestrone, and adenosine triphosphate exhibited the highest degree values, which are presumably the main active ingredients of velvet antler.The regulatory network comprising velvet antler for PMOP treatment is shown in We entered 233 common targets in the STRING database to obtain protein interaction relationships and drew PPI network diagrams. The PPI network ultimately contained 230 nodes and 4434 edges. The network topology analysis results were as follows: network density (0.157), network heterogeneity (0.799), and shortest path . According to the previous studies, the key core the lower limit should be twice the average degree of the nodes , 21. SinWe obtained the GO functional enrichment analysis of the 233 potential targets, and the results are shown in The 233 potential targets of velvet antler treatment of PMOP were enriched in 178 signaling pathways shown in . It can β-estradiol, oestrone, and adenosine triphosphate, which bind to key targets and exhibit scores <−5. The visual results of the docking of other targets are shown in We selected eleven core target genes with a support degree higher than 100 for molecular docking and analyzed the docking results, with Gscore used in the scoring of molecular docking; the lower the score, the stronger the binding force. A negative value indicated that the ligand molecule could spontaneously bind to the receptor protein, and a score <−5 indicated stronger binding activity. A total of three compounds were selected to be docked on eleven target proteins, and the molecular docking scores of the compounds are summarized in To estimate the effect of deer antler treatment on trabecular bone structure, trabecular architectural parameters were measured in the distal femoral bone by using micro-CT analysis . The BV/In the model group, the femoral shaft trabeculae were loosely distributed, the number of bone trabeculae was sparse, and the bone trabeculae showed low interconnectedness. The trabecular bone was thinner and thick locally. The distance between trabecular bones was augmented, and the proportion of the trabecular bone distribution area in the observation field was small. Compared with the model group, the number of trabecular bones in the femoral shaft of the deer antler group increased, and they were interconnected in a larger grid. The trabecular bones were locally thickened between the trabecular bones with the distance diminished. The trabecular bone distribution area accounted for the increase in the proportion of the observation field see .According to the quantification analysis from the H&E staining, supplementation of antler significantly increased the ratio of ObS/BS and significantly decreased the ratios OcS/BS and ES/BS, compared to those in the OVX group. There was no significant difference in the ratio change of OV/BV after three weeks of antler treatment . These rκB in response to RANKL. DAE also inhibited bone resorption and survival of osteoclasts [Deer antler has been reported to possess bone-strengthening activity and has been used in treating arthritis, osteoporosis, and avascular necrosis of the femoral head in animal models, and it plays pivotal roles in facilitation of proliferation and mineralization of osteoblasts. Wang et al. reported that deer antler type I collagen could induce BMSC differentiation into osteoblasts through the two signal transduction pathways, ERK1/2 and p38-MAPK, and can regulate the gene expression of Runx2 and Osx, which were specific transcription factors in this case . Yun et eoclasts . In addieoclasts . Thus, tβ-E2, adenosine triphosphate, and oestrone were important components in velvet antler for use in the treatment of PMOP, the primary component of which is cytoporosis. Lack of estrogen is the principal cause of PMOP, and estrogen replacement therapy can effectively improve the bone density of postmenopausal women with osteoporosis. Ge et al. [α activity [In the present study, we initially collected the effective ingredients of velvet antler and screened them. We then obtained genes that are differentially expressed in PMOP from the GEO database and OMIM database, constructed a drug-component-target-disease network, and further concluded that 17e et al.  demonstractivity  and can activity  and promactivity . ATP is activity . Miyazakactivity .We constructed KEGG and PPI networks based on target information and determined twenty-nine core targets based on their degree values. AKT1, IL6, MAPK3, TP53, EGFR, ESR1, SRC, TNF, STAT3, MAPK1, and JUN were the key target genes with higher-node degrees; these genes can be considered to be the core targets in the PPI network and may thus be the key target genes for velvet antler treatment of PMOP. AKT1 belongs to the protein kinase B gene family and is a key factor in the PI3K/AKT-signaling pathway; it can phosphorylate elements downstream to regulate cellular metabolism, proliferation, survival, growth, and many other processes. Researchers have demonstrated that after knocking out the rat AKT1 gene, rats showed limited bone development, indicating that AKTI may promote bone growth in bone development . Akt sigβ/Smad-signaling pathways [Achyranthes bidentata and Eclipta prostrata can regulate the ERK MAPK- and JNK MAPK-signaling pathways, respectively, to improve the former as major biomarkers of osteoblasts, and their augmented expression levels in turn promote the differentiation of BMSCs into osteoblasts.In this study, we used GO-enrichment and KEGG pathway-enrichment analyses to explore the multidimensional pharmacological mechanisms underlying the effects of velvet antler on PMOP. We also analyzed pathways containing other annotated genes, for example, viral infections with human cytomegalovirus, human papillomavirus, hepatitis B, human T-cell leukemia virus 1, and Kaposi sarcoma-associated herpesvirus. Based on this, we infer that velvet antler may have a broad-spectrum antiviral effect; and proteoglycans in cancer, prostate cancer, microRNAs in cancer, gastric cancer, breast cancer, and so on are mainly related to cancer. These approaches are not closely related to the treatment of postmenopausal osteoporosis with velvet antler. The PI3K/Akt- and MAPK-signaling pathways are two pathways that must be given more attention. The PI3K/AKT-signaling pathway is a key pathway for cellular proliferation and migration, and it is also a critical element in the development of osteoporosis. Overexpression of MIR-29b enhanced the proliferation and migration of bone marrow mesenchymal stem cells in ovariectomized osteoporotic rats, which may be due to the activation of PI3K/Akt- and TGF-pathways . The MAPpathways , and thepathways , 54 AchyWe then used molecular docking technology to verify the combination of eleven core targets and three primary components of velvet antler; our results show that the molecular docking score Gscore of the three main components and the core target is negative, indicating that the ligand molecule can spontaneously bind to the receptor protein, and the score <−5 indicates that the binding activity is stronger.Finally, in order to further confirm the results of the network pharmacology analysis, experimental verification was carried out using a postmenopausal osteoporotic mouse model. The structural and static histomorphometry parameters measure the microstructure and cellular components of the trabecular bone, respectively . Micro-Cβ-E2, adenosine triphosphate, and oestrone. These components act on key target genes, such as AKT1, IL6, MAPK3, TP53, EGFR, ESR1, SRC, TNF, STAT3, MAPK1, and JUN, and regulate the PI3K/Akt- and MAPK-signaling pathways. These molecules and pathways then participate in a series of processes, such as cellular differentiation, apoptosis, metabolism, and inflammation, and can ultimately be used to treat PMOP, reflecting the overall regulation, network regulation, and protein interactions. This study can provide a certain theoretical basis for the research and development of related drugs for the clinical treatment of PMOP. However, the regulation mechanism of its action still needs to be further verified through experiments.In this study, we used a combination of network pharmacology and molecular docking to explore the mechanism of action of velvet antler in the treatment of PMOP. The potentially effective components of velvet antler primarily included 17