Percutaneous coronary intervention (PCI) has become one of the effective methods for the treatment of coronary heart disease (CHD). However, it is easy to have in-stent restenosis (ISR), even cardiovascular events after PCI, which affects the therapeutic effects. The incidence of ISR in diabetes mellitus (DM) patients increased by 2 to 4 times. Early identification of the risk factors of ISR in DM patients after PCI may help clinical staff to prevent and intervene as soon as possible, so it is very important to improve the clinical outcomes of DM patients. Although scholars at home and abroad have studied and summarized the risk factors of ISR in DM patients after PCI, the conclusions are different. Therefore, in this study, meta-analysis was used to summarize the risk factors of ISR in DM patients after PCI, and to explore the characteristics of high-risk groups of ISR, thus providing reference for early identification and prevention of ISR.We will search related literature from PubMed, Embase, Cochrane Library, Web of Science, China Biology Medicine Database, China National Knowledge Infrastructure, China Science and Technology Journal Database, and Wanfang Database. Eligible studies will be screened based on inclusion criteria. Meanwhile, data extraction, risk of bias assessment, publication bias assessment, subgroup analysis, and quality assessment will be performed. Review Manager Version 5.3 software will be applied for data analysis. Each process is independently conducted by 2 researchers. If there is any objection, it will be submitted to a third researcher for resolution.We will disseminate the findings of this systematic review and meta-analysis via publications in peer-reviewed journals.The results of this analysis can be used to generate a risk prediction model and provide an intervention strategy for the occurrence of ISR in DM patients after PCI.DOI 10.17605/OSF.IO/WC87Y. At present, some scholars explore ISR from the aspects of drug type, stent type, and implantation technique, and have achieved fruitful results.,6 However, with the rapid development of PCI and the wide application of intravascular ultrasound, the indications of PCI are expanding, while the incidence of ISR is still increasing. However, at present, the mechanism of ISR is not clear, and many factors are involved in the occurrence and development of ISR.Percutaneous coronary intervention (PCI) has become a major treatment for coronary heart disease (CHD). DM patients have more complex coronary artery lesions, usually accompanied by dyslipidemia and abnormalities in the blood coagulation system.,10 DM patients are likely to develop ISR due to excessive intimal hyperplasia, excessive hemagglutination, increased inflammation, endothelial dysfunction, and complications.,12 Park et al proposed that the history of DM is an independent risk factor of ISR in patients after PCI. Some studies have proved that the risk of developing ISR in patients with diabetes is 2 to 4 times higher than that in ordinary patients.–17 The related predictors of ISR after PCI in DM patients are not clear. Therefore, as a high-risk group, DM patients have attracted more and more researchers’ attentions.At present, it is considered that bare metal stent, history of DM, residual stenosis after PCI, diameter, and length of stent are the influencing factors of ISR after PCI.–23 this paper makes a meta-analysis on the risk factors of ISR in DM patients after PCI for the identification the risk factors of ISR in DM patients after PCI, thus providing scientific basis for clinical prevention of ISR in DM patients after PCI.At present, there is no unified understanding of the pathogenesis, epidemiological status, diagnosis, and treatment of ISR in DM patients after PCI, and the research results of its risk factors are not same. In order to synthesize the results of previous studies,22.1https://osf.io/wc87y). This report will be based on the preferred reporting items for systematic review and meta-analysis protocols.This protocol has been registered on Open Science Framework grant number: DOI 10.17605/OSF.IO/WC87Y (2.2Inclusion criteria:1)Study design: We will include all observational studies  to analyze the correlation between risk factors and ISR in DM patients after PCI;2)Participants: 18 years and above adults with the ISR in DM patients after PCI will be included;3)Diagnosis of ISR: ISR, defined as coronary angiography, confirmed that the diameter of the lumen in the stent implantation segment and the proximal and distal 5 mm segments of the stent is more than 50% narrow;4)Outcomes: The results of the study involve the specific values of odds ratio (OR) and 95%confidence interval (95%CI) of risk factors.Exclusion criteria:1)The full text cannot be obtained normally or the extracted data are affected;2)Repeatedly published literatures;3)Review, systematic review, conference, animal experiments, and other literatures.2.3Electronic databases include PubMed, Embase, Cochrane Library, Web of Science, China Biology Medicine Database, China National Knowledge Infrastructure, China Science and Technology Journal Database, and Wanfang Database. The search terms have diabetes mellitus, ISR, in-stent restenosis, PCI, CHD, risk factor, risk assessment, multivariate analysis, and multivariable logistic regression. The search dates are from the establishment of the database to February 2021. These search terms are summarized in Table 2.4First of all, the original literature was screened by 2 researchers, and a third researcher judged whether to include the literature when having conflict opinions. Secondly, the full text was re-screened on the basis of the detailed entries of the literature inclusion criteria. Finally, the selected literature was analyzed by meta-analysis. The process of the selection is exhibited in Figure 2.5The literature data were cross-checked by 2 researchers and then imported into NoteExpress for collation. The main extraction contents include first author, year of publication, country, research type, study sample size, incidence of ISR, and risk factors.2.6 NOS score ≥ 5 means that the literature quality is better.Two authors will independently assess the quality of selected articles using the Newcastle-Ottawa Scale (NOS).2.7The data analysis of this study will be conducted through Review Manager Version 5.3 software. We will use OR and 95%CI to represent. If there are no findings of statistical heterogeneity, the fixed-effect model is adopted for data synthesis. If there is significant statistical heterogeneity, we will apply the random effect model. All participants will explore the possible causes from a clinical and methodological perspective and provide a descriptive or subgroup analysis.2.8χ2 test (the test level was α = 0.1) and combined with I2 to quantitatively determine the size of the heterogeneity. When P < .1 and/or I2 > 50%, the random effect model is adopted for the combined analysis. Otherwise, the fixed-effect model is used for the combined analysis.The heterogeneity included in the results of the study was analyzed by performing the 2.9According to the type and region of included literature, we make a subgroup analysis2.10To determine the stability of the outcome measures, each outcome measure was analyzed by performing sensitivity analysis.2.11We will evaluate the possibility of publication bias using funnel plots and Egger's test of bias will be took as a complement.2.12We will evaluate the strength of evidence for all outcomes by performing the Grading of Recommendations Assessment, Development and Evaluation working group methodology.2.13We will try our best to ensure the integrity of the data. If the included data is not complete, we will take every effort to contact the corresponding author of the article, including sending emails or making a phone call. If the corresponding author cannot be contacted, we will remove the experiment with incomplete data. After data integrity is assured, intention analysis therapy and sensitivity analysis will be performed.2.14The content of this article does not involve moral approval or ethical review and will be presented in print or at relevant conferences.3,29 The results of a large sample meta-analysis showed that DM was an independent risk factor of ISR. Abnormal glucose metabolism in DM patients often leads to insufficient insulin secretion or insulin resistance, which impairs the structure and function of vascular endothelial cells. Endothelial damage will stimulate the production of a large number of growth factors, and accelerate the proliferation of smooth muscle cells and inflammatory cells, thus promoting the proliferation of coronary artery intima. At the same time, the coagulation function of patients with DM is disordered, and platelets are easy to adhere to the damaged vascular endothelium to form thrombus, thereby narrowing the vascular lumen and the formation of ISR. Therefore, it is very necessary to study the risk factors of ISR in DM patients, a subgroup of high-risk groups.DM is an equal-risk condition of CHD. The prognosis of CHD patients complicated with DM was worse and the fatality rate was higher.At present, the research on ISR in DM patients after PCI at home and abroad is mainly single-factor and single-center research, while large sample size and multi-center research are few, and the conclusions are different. Therefore, this paper carries out meta-analysis on the risk factors of ISR in DM patients after PCI to provide clinical basis for early prevention of ISR in DM patients after PCI.This study has the following limitations: there are differences in race, number of cases, research tools and regions of this study, and there is a certain heterogeneity after the combination of some risk factors. The purpose of this system review and meta-analysis is to clearly identify important risk factors for ISR in DM patients after PCI, thus providing prevention strategies. Most importantly, this study will assess new and controversial factors because of their potential as prevention targets.Conceptualization: Suiping Li and Haimei Chen.Data collection: Suiping Li.Data curation: Suiping Li.Formal analysis: Chao Luo.Funding acquisition: Haimei Chen.Investigation: Chao Luo.Project administration: Haimei Chen.Resources: Haimei Chen.Software: Chao Luo.Supervision: Chao Luo, Haimei Chen.Validation: Chao Luo.Writing – original draft: Suiping Li and Haimei Chen.Writing – review & editing: Suiping Li and Haimei Chen.


Background: Arterial stiffness was the pathological basis and risk factor of cardiovascular diseases, with chronic inflammation as the core characteristic. We aimed to analyze the association between the arterial stiffness measured by cardio-ankle vascular index (CAVI) and indicators reflecting the inflammation degree, such as count of leukocyte subtypes, platelet, and monocyte-to-lymphocyte ratio (MLR), etc.Methods: The data of inpatients from November 2018 to November 2019 and from December 2019 to September 2020 were continuously collected as the training set  and the validation set (700 cases), respectively. A retrospective analysis of gender subgroups was performed in the training set. The association between inflammatory indicators and CAVI or arterial stiffness by simple linear regression, multiple linear regression, and logistic regression was analyzed. The effectiveness of the inflammation indicators and the CAVI decision models to identify arterial stiffness by receiver operating curve (ROC) in the training and validation set was evaluated.Results: The effect weights of MLR affecting the CAVI were 12.87% in men. MLR was the highest risk factor for arterial stiffness, with the odds ratio  of 8.95 (5.04–184.79) in men after adjusting the covariates. A cutpoint MLR of 0.19 had 70% accuracy for identifying arterial stiffness in all participants. The areas under the ROC curve of the CAVI decision models for arterial stiffness were >0.80 in the training set and validation set.Conclusions: The MLR might be a high-risk factor for arterial stiffness and could be considered as a potential indicator to predict arterial stiffness. Arterial stiffness is characterized by degradation in the extracellular matrix of the mediator layer, while atherosclerosis is caused by the accumulation of lipids in the intimal layer initiating the migration of inflammatory cells . Arteriahttps://doi.org/10.7910/DVN/SGHUV2. This was a retrospective, cross-sectional study, and all samples do not contain personal identification. We were unable to obtain written consent from all patients. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki.All materials have been made publicly available at the HARVARD Data verse and can be accessed at We evaluated the arterial stiffness risk of the indicators and constructed CAVI decision models in the training set. The predictive capability for arterial stiffness of the multiple regression models was constructed in the training set, and these indicators were validated in the training set and the validation set.To construct the decision model of CAVI, the data of patients who were hospitalized in the General Medical and Geriatrics Department of Wuhan Union Hospital from November 2018 to November 2019 and accepted arterial elasticity measurements were collected as a training set. And data from December 2019 to September 2020 were applied to verify the identifying validity for arterial stiffness of the indicators and the constructed models. Samples where the leukocyte subtype counts or ratio may be severely affected by diseases or medicine were excluded. The specific exclusion criteria are as follows: (1) definite or suspicious blood system diseases, such as infectious mononucleosis, leukemia, and lymphoma, etc.; (2) currently or recently used immunosuppressive agents, such as cyclophosphamide, cyclosporine, etc.; (3) suffering from autoimmune diseases that seriously affect the number of white blood cells, such as systemic lupus erythematosus and Graves disease; (4) severe hypersplenism; (5) taking medication that may affect the white blood cell count or infusing blood; (6) suffering from other malignant tumors and are undergoing radiotherapy or chemotherapy.The participants' smoking and alcohol history and clinical diagnosis including HTN and diabetes mellitus (DM) were collected simultaneously. Ten milliliters of venous blood in the fasting state in the morning after the patients were admitted to the hospital were obtained, and the samples were sent to the laboratory immediately. Blood counts were evaluated by BC-3000 auto hematology analyzer . Then, the NLR, MLR, and PLR as the ratio of neutrophils to lymphocytes, monocytes to lymphocytes, and platelets to lymphocytes were calculated, respectively. The levels of uric acid, triglycerides (TGs), cholesterol (CHOL), low-density lipoprotein, and fasting blood glucose were determined by Union Hospital's standard biochemical index laboratory measurement procedure. The NLR, MLR, and PLR were calculated as the ratio of neutrophil count to lymphocyte count, monocyte count to lymphocyte count, and platelet count to lymphocyte count, respectively.The CAVI adopts the pulse-wave algorithm and utilizes the stiffness parameter β to reduce the influence of blood pressure fluctuations on the detection of vascular elasticity. The arterial elasticity of the patient was measured with the VS-1000 AS tester of Japan Foton Company. The patient rested quietly for about 15 min before the examination and then measured in the supine position. The blood pressure of the extremities at the position of the upper arm and ankle arteries was measured, and the electrocardiogram, heart sound graph, and pulse-wave waveform were recorded at the same time. The bilateral CAVI (m/s) value was calculated, and the average of the measured values on both sides was employed in the study. Arterial stiffness is considered as CAVI ≥9 (m/s); otherwise, it is non-arterial stiffness (non-AS).U test and t test were used to compare the difference between non-AS and AS in non-normal distribution and normal distribution quantitative data, respectively. A χ2 test was used to compare the difference of categorical data between the groups. Analysis of covariance (ANCOVA) is used to compare continuous variables between groups after adjusting for confounding factors. The inflammatory indicator difference was tested between AS and non-AS on the sample set after implementing confounding variables by individually pair-matched case–control analysis. The scatter plots were drawn between CAVI and each inflammation indicator, and the fitted linear lines for each inflammation indicator were calculated. The multiple regression analyses were performed using the stepwise backward method to determine the contribution size of inflammation indicators and clinical variables to arterial stiffness. The odds ratios (ORs) and 95% confidence intervals for arterial stiffness were calculated with logistic regression after adjustment for covariates that may affect arterial elasticity. A subgroup analysis of inflammatory indicators to AS risk in people with different clinical pathophysiological characteristics was carried out. Finally, the receiver operating characteristic (ROC) curves were determined to assess discrimination of these indicators and final multiple regression models to diagnose arterial stiffness. p < 0.05 was considered statistically significant. All calculations and graphs were done using R (version 3.6.3-Mac OS X 10.11).Quantitative data of non-normal distribution and normal distribution were expressed as medians with interquartile range and mean ± SD, respectively. Categorical data were expressed as amounts with percentages. The Mann–Whitney The training set and the validation set included 1,089 and 700 sample materials, respectively. The materials stratified by arterial stiffness are summarized in p < 0.001), NE (p < 0.001), MLR (p < 0.001), NLR (p = 0.003), and PLR (p = 0.034) remained significant differences in the group of AS and non-AS, whereas PLT (p = 0.063) and LY (p = 0.914) were not significantly different between the groups , monocytes (MO), NLR, MLR, and PLR of participants with arterial stiffness were significantly higher than those of patients without arterial stiffness, whereas lymphocytes (LY) and platelets (PLT) were lower in the AS group. Then, with age, sex, BMI, TGs, CHOL, HTN, and DM as covariates, which show a significant difference between the AS and non-AS groups, we further performed the ANCOVA to test the differences of leukocyte counts and their ratios between patients with and without AS. The results indicated that after adjusting the confounding variables, MO . The results indicated that only NLR and MLR showed the significant risk for AS in all subgroup analyses, and the risk value of MLR  was much higher than NLR (OR = 1.29–1.93) .p > 0.05), and their AUCs were all 0.87 in the training set and 0.80–0.84 in the validation set  in men, but it was non-significant in women (p > 0.05); the efficacy of MLR in suggesting arterial stiffness in men is better than in women (AUC = 0.72 vs. 0.67). The intimate association between MLR and CAVI in men may confirm the fact that men are more susceptible to ischemic heart disease of large vessels than women  can be found below: Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.BQ: conceptualization. RW, YW, YL, LB, LL, and LH: methodology and data collection. YW: data curation, formal analysis, visualization, and writing—original draft. RW: supervision and writing—review & editing. 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.


Post-antibiotic intestinal dysbiosis leads to an overall reduction in bacterial and functional diversity, along with a minor resistance against pathogens. The study aimed to determine the changes on the fecal microbiota in hospitalized neonatal foals administered with broad-spectrum antimicrobials and supplemented probiotics. Fecal samples were collected at hospital admission, at the end of the antimicrobial treatment and at discharge. Seven foals treated with intravenous ampicillin and aminoglycosides for a mean of seven days were included. The results suggest that the fecal microbiota of neonatal foals rapidly returns to a high diversity after treatment. While the findings need to be confirmed in a larger population, the study suggests that in foals, the effect of antimicrobials may be strongly influenced by the changes that occur over time in the developing gut microbiota. Of note, the findings are influenced by the use of probiotics, and whether the changes would be consistent in antimicrobial-administered but not supplemented foals remains to be elucidated.Akkermansia over time was detected. The results suggest that the intestinal microbiota of neonatal foals rapidly returns to a high diversity after treatment. It is possible that in foals, the effect of antimicrobials is strongly influenced or overshadowed by the time-dependent changes in the developing gut microbiota.There is a wide array of evidence across species that exposure to antibiotics is associated with dysbiosis, and due to their widespread use, this also raises concerns also in medicine. The study aimed to determine the changes on the fecal microbiota in hospitalized neonatal foals administered with broad-spectrum antimicrobials and supplemented probiotics. Fecal samples were collected at hospital admission (Ta), at the end of the antimicrobial treatment (Te) and at discharge (Td). Feces were analysed by next-generation sequencing of the 16S rRNA gene on Illumina MiSeq. Seven foals treated with IV ampicillin and amikacin/gentamicin were included. The mean age at Ta was 19 h, the mean treatment length was 7 days and the mean time between Te and Td was 4.3 days. Seven phyla were identified: Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, Proteobacteria, TM7 and Verrucomicrobia. At Ta, Firmicutes (48.19%) and Proteobacteria (31.56%) were dominant. The alpha diversity decreased from Ta to Te, but it was the highest at Td. The beta diversity was higher at Ta than at Te and higher at Td than at Te. An increase in  Neonatal foals are predisposed to life-threatening bacterial infections, and antimicrobials are routinely and widely employed in equine neonatal medicine, either prophylactically or therapeutically . Sepsis While the use of perinatal broad-spectrum antibiotics is common, there is wide evidence that early exposure to antibiotics is associated with dysbiosis and long-term impacts on microbial diversity and health, with derangement in the development of the immune, metabolic and nervous system in humans ,6,7. DysAntimicrobial-associated dysbiosis leads to an overall reduction in bacterial and functional diversity, along with a minor resistance against pathogens ,11 and tThe diverse effect on bacterial taxa is strikingly dependent on the antimicrobials classes and combinations used. This effect may be due not only to the nature of the agent itself, but also depends on other factors including dose and route, period of exposure, pharmacokinetics, pharmacodynamic and the stability of the microbiota itself ,14,15,16Nevertheless, the gut microbiota has a variable degree of resilience, which allows recovering to pre-treatment conditions after the balance has been disrupted. However, studies suggest that this recovery might not be complete at least over a long period , and thiAntimicrobial-associated dysbiosis also raises concerns in equine neonatal medicine. In foals, the development of post-natal microbiota has been investigated by Next Generation Sequencing (NGS), and it is characterized by a high instability and rapid changing over time ,22,23,24With respect to culture-dependent techniques, molecular approaches dramatically improved the ability to examine gut microbiota composition and dynamics related to antimicrobials administration .A few reports exist exploring the effects on gut microbiota of a broad-spectrum antimicrobial therapy in adult horses ,26,27,28This study aimed to determine changes related to broad-spectrum antimicrobials administration on the fecal microbiota (FM) of hospitalized neonatal foals by means of NGS of the 16S rRNA gene. Fecal microbial ecosystem was characterized with regard to relative abundance at mean and individual levels before and after administration of a broad-spectrum antimicrobial treatment in foals hospitalized for common neonatal pathologic conditions . Moreover, biodiversity changes in gut microbiomes and their relationship with the antimicrobial treatment were analyzed.The study was conducted at the Equine Perinatology Unit (EPU) of the Veterinary Teaching Hospital of the University of Bologna during the foaling season 2019.All procedures on the animals were carried out according to the ethics review committee at the University of Bologna. Oral informed consent was given by the owner for each animal.Fecal samples were collected from hospitalized neonatal foals administered a broad-spectrum antimicrobial treatment either therapeutically or prophylactically. At enrolment, foals should have no history of antimicrobials administration, and dams of the foals should have not received antimicrobials in the last three months. Enrolled foals were either born from mares hospitalized at the EPU for attended delivery or hospitalized after birth.Pregnant mares were hospitalized at about 310 days of gestation. They were judged clinically normal based on daily physical examination, complete blood count (CBC) and serum biochemistry at admission, and periodical ultrasonographic monitoring of feto-placental wellbeing was conducted upon foaling. Foals received a full diagnostic protocol including: full physical examination, CBC and biochemistry, arterial blood gases analysis, serum IgG and blood lactate concentration and blood culture. Foals born at the EPU were also assessed at birth by means of an Apgar score [Diagnostic criteria were defined as follows.Failure of passive transfer of immunity was diagnosed as blood IgG concentration < 800 mg/dL after 18 h of life .positive blood culture;positive culture of samples from local sites of suspected infection;postmortem examination. Systemic inflammatory response syndrome (SIRS) diagnosis was made as suggested by Wong and Wilkins .Foals were classified as septic in the presence of both infection and systemic inflammatory response . InfectiFoals were classified as affected by Perinatal Asphyxia Syndrome (PAS) on the basis of clinical history , clinical signs  and laboratory abnormalities .Foals were defined as premature if born prior to 320 days gestation and were defined as dysmature if born after 320 days but with immature physical characteristics  ,36. FoalAccording to clinical management, foals and their dams were housed in single, wide, straw-bedded boxes, either together or separated by a gate allowing contact, and foals were fed mare’s milk and/or milk replacer during the hospitalization. They were turned out during the day only where applicable. Mares were fed hay ad libitum and 14–16% sweet feed concentrates.before the start of antimicrobial treatment ;at the end of the treatment (Te);the day of discharge from the hospital (Td).Fecal sampling was planned at three time points: ampulla and from the center of the fecal material [At least 2 g of feces were collected from the rectal material . The samTo the study purposes, the following data were recorded: diagnosis, age (hours) at the start of antimicrobial treatment, antimicrobial treatment duration (days), time from the end of treatment to the hospital discharge , antimicrobials (dosage and route), occurrence of diarrhoea and further treatments . Moreover, source of milk feeding  during the observation period was recorded for each foal.Bacterial DNA was extracted from stools with a DNeasy Blood & Tissue kit  as previously described by Biagi et al. , adding DNA samples were quantified using the NanoDrop ND-1000 .The V3–V4 region of the 16S rRNA gene was amplified by means of the primer set S-D-Bact-0341-b-S-17/S-D-Bact-0785-a-A-21  carryingAmplicons were purified with a magnetic bead-based clean-up system . Indexed libraries were prepared by limited-cycle PCR using Nextera technology and further cleaned up again by the magnetic bead-based clean-up system. Final libraries were pooled at 4 nM, denatured and diluted to 6 pM before loading onto the MiSeq flow cell . Sequencing was performed by a 2 × 300 bp paired end protocol, according to the manufacturer’s instructions  .http://metagenomics.anl.gov/mgmain.html?mgpage=project&prject=59129e34be6d67703833303632 accessed on 12 September 2019).Amplicon sequences were deposited in the MG-Rast database (http://rdp.cme.msu.edu/ accessed on 12 September 2019) against Greengenes database from May 2013 release (http://greengenes.secondgenome.com/downloads) .Raw sequences were analyzed using Quantitative Insights Into Microbial Ecology (QIIME) version 1.9.1 . Reads wFor the OTU sharing analysis, OTUs representing more than 0.01% of the total OTU number were considered.http://www.R-project.org/) on Rstudio v1.1.456 (RStudio Team (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/) where all statistical analyses were performed. A p-value < 0.05 after False Discovery Rate (FDR) correction was considered as statistically significant. Alpha diversity was evaluated by calculating Observed species, Chao1, Shannon, ACE (Abundance-based Coverage Estimator), Inverse Simpson’s and Fisher’s indices using R package phyloseq [The bacterial abundance data were imported into R , was pephyloseq . To idenphyloseq .Seven hospitalized neonatal foals that had received the same association of antimicrobials (ampicillin combined with an aminoglycoside IV) and had a complete sampling series were available for analysis.The demographic and clinical data regarding the individual foals are presented in E. coli isolated from blood culture), dysmaturity and FPT. Two foals were treated prophylactically for PAS, three foals for FPT and one for PAS and FPT.The mean age at Ta was 19 h (0–42 h). All seven foals received ampicillin (50 mg/kg IV QID) combined with an aminoglycoside , therapeutically or prophylactically, according to their diagnosis. One foal (CM) had a diagnosis of sepsis , and the mean time between Te and Td was 4.3 days (1–9 d).The treatments and management were tailored on an individual basis according to the clinicians’ judgement. All the foals received probiotics  for the duration of the antimicrobial treatment. As shown in Four foals developed a mild diarrhea, which was not further investigated, without major complications: three during the antimicrobial treatment  and one after the end of the treatment (FDT). Three foals received a fecal microbial transplantation (FMT) during the diarrhea; in two of the three cases, the donor was the dam, and in one case, the donor was a foster mare. The diarrhea did resolve in all cases within hospital discharge.Two of the seven foals received a milk replacer along with dam’s milk during the observation period; one orphan foal (TR) received milk replacer and milk from a foster mare, and feces from the same foster mare were provided for coprophagy. All the other foals had access to their dams’ feces during the hospitalization.All foals were diagnosed as clinically normal at discharge from the hospital.The analyzed samples included 4 samples of meconium at Ta  and 17 fecal samples at Ta, Te and Td. Sequencing of the 16S rRNA gene yielded 188.027 high-quality reads .All bacterial OTUs detected at a relative abundance greater than 2% were figured in bar plots of fecal microbiota composition of the foals at the three timepoints in relation to the antimicrobial therapy. The remaining OTUs were classified as “other” and unclassified bacteria group under the definition “unassigned_other”. All bacterial OTUs with their relative abundance detected at the three timepoints are reported in Mostly, no significant differences were found in the relative abundances between timepoints at the family nor at the genus level, and the results are reported as trends.The relative abundance of bacterial OTUs at genus levels in the seven foals across three timepoints are plotted in Bacterial OTUs were clustered into seven different phyla: Firmicutes (48.1%), Proteobacteria (31.56%), Bacteroides (7.55%) e Actinobacteria (4.48%), Verrucomicrobia (1.79%), with TM7 and Fusobacteria (less than 1%) .Enterococcus (13.23%) were the most prevalent. Other taxa included were Pseudomonas (6.33%), Streptococcus (5.30%), Bacteroides (4.76%), genera within the family Clostridiaceae (4.90%) including Clostridium, Peptostreptococcaceae (3.56%) and Epulopiscium (2.40%). Genera of the Akkermansia and Lactobacillus and Ruminococcaceae families were identified at a relative abundance < 2%.At a family level, Enterobacteriaceae and Enterococcaceae had the more represented mean relative abundance (17.55% and 13.23%), followed by a decreasing contribution of Lachnospiraceae (7.07%), Pseudomonadaceae (6.40%), Clostridiaceae (6.29%), Streptococcaceae (5.32%), Bacteroidaceae (4.78%) and Ruminococcaceae (3.80%). At a genera level, genera owing to Enterobacteriaceae (17.08%) and In comparison to Ta, fecal samples collected at Te showed a trend of reduction in the phyla Firmicutes (38.93%) and Actinobacteria (3.03%), which were replaced by an increment of Verrucomicrobia (3.95%), Fusobacteria (3.44%), Bacteroidetes (11.37%) and Proteobacteria 11.44%) .p = 0.02) and a tendency to increase in Bacteroidaceae  and Verrucomicrobiaceae , along with a trend to reduce in Clostridiaceae , Pseudomonadaceae (0.19% p = 0.33)—which almost disappeared—and Mogibacteriaceae (p = 0.34).On a family level, a loss of microbial diversity was noted. In particular, the main changes were an increase in Enterobacteriaceae , Bacteroides , Fusobacterium , Akkermansia  and Streptococcus  were all represented with a tendency to increase in average abundance.Coming to genera, a trend to reduction in the overall microbial diversity was still evident, along with a prevalence in the relative average abundance of members of the Enterobacteriaceae (35.94%). Genera such as Samples at Td showed a trend to an increased mean relative abundance in the phyla Firmicutes (61.58%) at most, Verrucomicrobia (10.28%) and Actinobacteria (6.35%), while it was lower for Proteobacteria (11.44%), Bacteroidetes (7.66%) and Fusobacteria (0.82%) compared to Te. .p = 0.035), Verrucomicrobiaceae , Clostridiaceae  and Mogibacteriaceae  tended toward a higher mean abundance with respect to Te; on the contrary, Enterobacteriaceae  and Bacteroidaceae  were less represented.The families Lachnospiraceae , Lactobacillus (7.41%), Ruminococcus , Clostridium (3.90%) and Bifidobacterium  showed a tendency to increase compared to Te, while the genera Bacteroides , Enterococcus  and Streptococcus  tended to be lower than Te.At a genera level, the mean relative abundance of Akkermansia  and members of the Mogibacteriaceae  after antibiotic treatment, while the family Enterobacteriaceae showed later, between the end of therapy and the time of discharge, only a trend to increase.Finally, when microbiota composition was analyzed throughout time, DeSeq analysis detected a significant increase in In order to compare the alpha diversity of the microbial ecosystems among foals at the three timepoints, the richness indices Observed species and Shannon were plotted .p-value FDR-corrected = 0.052).Species richness was variable across samples at all the three timepoints. Overall, Te showed a trend toward a lower level of biodiversity compared to Ta. Afterwards, albeit not significantly, Td appeared to be the most diverse, with a species richness tending to be higher than the initial condition .The box represents the interquartile ranges (IQR) containing 50% of the samples, the horizontal line in a box represents the median, whiskers represent maximum and minimum within 1.5 × IQR and circles represent outliers. No significant differences were found between timepoints . Indeed, a qualitative reduction of microbial communities was observed across the samples. The results from PCoA analysis show that at Te, the foals’ gut microbial ecosystems inter-individual variability is smaller when compared to Ta or at discharge (Td). The picture is in agreement with the literature, showing that any antimicrobial will have an effect on the overall host flora—the intestinal flora in particular—and not only on the bacterial target .The perturbation of gut microbial communities depends on antimicrobial class, dose and period of exposure, as well as their pharmacological action on the target bacteria . In adulInterestingly, the most profound impact on fecal microbiota has been reported from days 2 to 5 in adult horses when different antimicrobials are administered ,27,28. AWhen the FM composition in terms of the taxa’s relative abundance was observed, a large inter-individual variability characterized the microbial ecosystems during the whole study period. Some trends of change were identified comparing samples before and after antimicrobial treatment. A tendency to a decrease for Firmicutes and increase for Verrucomicrobia after the treatment is in line with reports in humans, where these phyla represent, overall, the most sensitive and resistant phyla to antimicrobials, respectively . MoreoveA decrease in Verrucomicrobia was similarly found after 3 days of oral metronidazole in adult horses . In contAkkermansia, which showed a significant increase in abundance, in line with its mentioned resilience. Indeed, Akkermansia has been shown to appear early in the gut microbiota and increase throughout time in newborn foals [Akkermansia is associated with intestinal integrity, and its metabolic activity influences short-chain fatty acids (SCFA) production contributing to the gut health [In the present study, the phylum Verrucomicrobia was dominated by the genus rn foals ,23,24, arn foals ,54. Akket health .Enterobacter spp., in particular—has been reported in babies receiving early antimicrobials, and more specifically, the combination of ampicillin and gentamicin [In this study, the only significant change was the higher abundance of the members of Enterobacteriaceae after antimicrobial treatment. This change is consistent in the human literature, where an increase in Enterobacteriaceae—ntamicin ,16,52,56ntamicin .Faecalibacterium and Blautia was found, similarly to findings induced by the same antibiotics’ association in murine models [A reducing trend in e models . These ge models .Bifidobacterium and Bacteroides tended to be more abundant after treatment. These two genera have been reported as being sensitive to the highest number of antimicrobials and combinations in humans [Bifidobacterium is another important genus implied in gut protection and immunologic and inflammatory processes in humans [In opposition with the human literature, n humans . A reducn humans  and in mn humans . Differen humans . Bifidobn humans . It is cn humans , and in Bacteroides—has been observed on the 11th day after treatment with beta lactams in humans, although they were more metabolically active already since the 6th day [Bacteroides has been shown in adult horses [Nevertheless, consistent with the present findings, a shift towards Bacteroidetes—and mainly  6th day . Furthert horses .Streptococcus and Ruminococcus tended to increase with the combination of antibiotics used in this study. Albeit Streptococcus spp. also figures among the most sensitive to several classes of antibiotics used in humans, and Ruminococcus decreased in mice treated with ampicillin and gentamicin [The genera ntamicin , it was ntamicin .Overall, antimicrobial administration in neonatal foals tends to decrease cellulolytic and fibrolytic bacteria, and the microbiota disruption might lead to a proliferation of pathogenic bacteria, which is in line to what it has been described in adult horses .With regard to the findings at discharge, despite only a few days passing since the end of the treatment, as the foals were rebuilding up their gut flora, a trend to gain a higher microbial diversity was already observed.The literature is relatively consistent across species in reporting that the gut microbiota has a degree of resilience, yet a variable amount of time is needed to recover the pre-treatment or health-associated gut ecosystem. In particular, in babies, an incomplete recovery of the gut microbiota has been observed months after cessation of the treatment, and after weeks in mice . In adulIn the present study, a new increase in microbial diversity seems to occur faster than in adult horses, as the earliest samples were only two days from the end of the treatment. Costa et al.  suggesteEubacterium) which were characteristic of the pre-treatment samples have reappeared at discharge. This is consistent with a trend toward reestablishing an eubiotic setting of the gut ecosystem after recovery from antimicrobials, where fibrolytic and SCFA productor taxa are dominant over pathobionts. In this contest, Akkermansia figures also as a leading microorganism at discharge.In Noteworthy, since microbiota in neonates is not yet fully developed and established, it is reasonable that the effects of antibiotics treatment cannot be expressed as a measure of return to the pre-treatment state. In the PCoA analysis, a shift of the ellipse is visible, meaning that bacterial communities are different between the pre-treatment time and the time of discharge from the hospital in our population. Furthermore, a higher convergence of the samples is depicted at discharge.This may be a selective effect of the antimicrobials administration itself. Indeed, the perturbations induced may cause a permanent shift in the ecosystem or lead toward a different developmental trajectory. In humans, the sequence of bacterial colonization is important in shaping the gut microbiome, so it has been suggested that early antimicrobial-associated changes may have long term effects . NeverthOverall, the small number of enrolled foals represents a main limitation of the study and might have impaired the ability to detect significant changes in the fecal microbiota associated to antimicrobial administration. Regardless, as it was already suggested by Costa et al. , the cliFurthermore, many confounding factors may have played on the results observed in the present population, rendering an interpretation of the findings with regard to genuine effects of antimicrobials is not straightforward. First of all, as mentioned above, a leading effect of age-related change in the gut microbiota. Although we attempted to reduce some of the age-related variability by enrolling only foals within 48 h of life, the neonatal gut microbiota is characterized by a highly variable and dynamic flora, following its trajectory toward an adult-like gut microbiota, with rapid changes happening in the period encompassed by the study ,23,24,25Blautia and Ruminococcus [If we compare the pre-treatment gut microbiota composition with a previous study conducted on healthy neonatal foals born at the same hospital, although there is concordance on the main phyla represented, they differ in their relative abundance, in particular, for Fimicutes and Proteobacteria , which mnococcus , and thiAs it is reported in adult equines , many otLactobacillus and Bifidobacterium in neonatal foals receiving a multistrain probiotics product. In this study, a different product was used, and there was a tendency to increase in Lactobacillus and Bifidobacterium throughout time, which, as already discussed, is in contrast with findings associated with antimicrobials exposure in most of the human literature [In addition to the inherent animal factors, there are a number of other factors related to the clinical condition and hospitalization to consider. All the foals received a probiotic product during the antimicrobial treatment or even the whole hospitalization. The effects of probiotics on the microbiota changes could not be determined nor discriminated in the present population, and further studies are needed to compare foals administered broad-spectrum antimicrobials with or without probiotics supplementation. Overall, the evidence for probiotics use in horses and foals is not consistent ,19,28,66In spite of the administration of probiotics, four out of the seven foals developed a mild diarrhea either during or after the antimicrobial treatment. Foal diarrhea shows a high frequency in the first 6 months, and often the etiology remains undetermined . As prevAlthough it is speculative, we think it is intriguing that the four foals developing a diarrhea were the same ones which received prophylactically omeprazole. Omeprazole administration has been associated with a higher risk of diarrhea in neonatal foals . AvailabNotably, three of the four foals received one to three fecal microbiota transplantations (FMT) during the course of diarrhea, which was considered effective in all cases. While the use of FMT in adult horses with diarrhea has been recently evaluated by means of NGS , to the Enterococcus faecalis over time [A last factor the authors think is worth commenting on is the milk source, which was not uniform among foals. In the human literature, a less diverse, with less potential pathobionts, has been reported in breast-fed babies with respect to formula-fed babies . Howeverver time . To the Overall, there are multiple potential confounding factors on the findings, which could not be controlled in the setting of the present study, should be evaluated by comparison of larger sample sizes where clustering of subjects by these factors would be possible. As it is in humans, the large inter-individual variability in the microbiota composition prompts multiomic approaches to explore its functionality and host-interaction .Overall, the findings of this small-scale study are not conclusive but tend to be in line with the acknowledged antimicrobial-associated gut microbiota modifications in human medicine. A trend to a generalized loss of alpha diversity was observed after IV ampicillin-aminoglycoside administration and supplementation with probiotics. A degree of unbalance of the relative abundances toward pathobionts over beneficial SCFAs producers was observed but could not be confirmed. This general picture tended to revert toward a more eubiotic setting after a few days of recovery. A relatively high beta diversity observed at this time might be expected, due to the highly dynamic changes occurring in the gut microbiota in foals of this age. It is possible that in this population of foals, the effect of antimicrobials is strongly influenced and possibly overshadowed by the changes that occur over time in the developing gut microbiota. While multiple limitations and confounding factors prevent the authors from drawing conclusions, especially in terms of changes to the microbial taxa, these preliminary findings suggest a general trend characterized by a loss of fecal microbial diversity after a short course of broad-spectrum antimicrobials administration followed by a rapid increase after antimicrobials have been interrupted. Of note, the findings are influenced by the use of probiotics, and whether the changes would be consistent in antimicrobial-administered but not supplemented foals remains to be elucidated. The effects of a different treatment duration and recovery period could be different. The relationship between fecal microbiota and animal-inherent factors and pathological conditions, the impact of FMT as well as other external factors related to hospitalization warrant investigations in larger populations and homogenous groups of foals.


Trichosanthes extracts on the hyperglycemic condition in streptozotocin- (STZ-) induced diabetic rats. The blood glucose levels, body weights, water intake, and urine volumes of rats in different experimental groups were monitored throughout the experiment, and the results obtained indicate that the two extracts can effectively reduce blood sugar levels, increase body weights, and improve water intake and urine volumes in diabetic rats. Based on blood biochemical analyses, the two extracts play an important role in regulating the diabetes-induced lipid metabolism disorder, increasing the levels of insulin and C-peptide, and alleviating the symptoms of diabetes. The variation in the liver glycogen contents of the water-soluble fraction and ethanol fraction groups suggests that the mechanisms underlying the hypoglycemic effects of the two extracts are different. Indeed, the water-soluble fraction alleviates diabetes symptoms in rats mainly by antioxidative activity, unlike the ethanol fraction.This study investigates the effects of the water-soluble and organic-soluble  Type 1 diabetes mellitus (T1DM) is an organ-specific disease mediated by autoimmune deficiency and the selective destruction of islet B cells . T1DM acTrichosanthes (the root of Trichosanthes kirilowii Maxim. in Cucurbitaceae family) can relieve thirst, body heat, distemper, great heat, tonify deficiency and ease the middle, and continue to eliminate injury. Moreover, in Li's Compendium of Materia Medica, Trichosanthes was record as the holy medicine for relieving thirst [Trichosanthes is actually included in 143 out of 592 traditional Chinese medicine prescriptions used for the treatment of diabetes, and thus, it is the fourth-ranking active ingredient. In addition, the use frequency of Trichosanthes-containing prescriptions exceeded 50%, which shows that in traditional Chinese medicine, this plant is of great significance for the treatment of diabetes [In ancient times, diabetes was called Xiaoke lesion, and it was treated using different kinds of traditional Chinese medicines. The Shennong Materia Medica reported that among the used medicines, g thirst . Trichosdiabetes . ConsequTrichosanthes in an STZ-induced type 1 diabetic rat model. Through this study, we could develop more therapeutic drugs for T1DM. More importantly, our research data is a supplement to the previous research, which can provide more accurate research data for later clinical development and application.In this study, we assess the immune intervention effects of the water and alcohol extracts of T. kirilowii Maxim. was cultured in Linyi  and harvested in August 2019. The drug was authenticated by a botanist at the Shandong University of traditional Chinese Medicine, Jinan. The fresh roots were washed, sundried, and stored in plastic bags at room temperature until further use. The antibodies were purchased from Affinity Inc. .Male Sprague-Dawley (SD) rats  were provided by the Shandong University Experimental Animal Center . STZ was purchased from Sigma-Aldrich . All of the other chemicals and reagents were obtained from general commercial sources , and they were used as received, unless otherwise specified. T. kirilowii Maxim. roots were sliced, crushed, and boiled in pure water for 2 hours , and the resulting aqueous solution was purified with diatomite and concentrated. Subsequently, the concentrate was freeze-dried to obtain the water-soluble fraction. To prepare the ethanol fraction, the T. kirilowii Maxim. roots were first boiled in anhydrous ethanol ; then, the solution was concentrated and vacuum dried.T. kirilowii water extract solution by gavage. This solution was prepared by dissolving the freeze-dried water extract in pure water and then filtering through a 0.22 μm membrane, and it was stored at 4°C prior to use. Meanwhile, the ethanol fraction group was given daily doses of 20 mg/kg ethanol extract solution (extract dissolved in a 2 : 8 v/v ethanol : water mixture), also by gavage. The rats in the sham group and diabetes mellitus (model) group were administered with normal saline by gavage, according to the same schedule. After five weeks, the rats were weighed; then, they were anesthetized with phenytoin sodium. Their livers and skeletal muscles were collected, and their blood was collected from the celiac artery. The serum was obtained by centrifugation at 2250 × g and 4°C for 20 min, and it was used for biochemical analysis.The animal experiments were conducted in accordance with the Chinese National Guide for the Care and Use of Laboratory Animals and approved by the ethics committee of Linyi University. The male SD rats were kept in a pathogen-free animal room where they were subjected to 12 : 12 h light/dark cycles. The animals were randomly divided into four groups , with 10 rats in each group, and they were acclimated to the environment for one week before experimentation. After the acclimation period, the rats were administered with daily injections of 55 mg/kg body weight STZ in normal saline . The bloThe oral glucose tolerance test (OGTT) is an important indicator of diabetes; so, it was performed on the experimental animals in this study . One dayThe body weights and blood glucose levels of rats in different groups were measured and recorded every week. Similarly, changes in the amount of water consumed were monitored, and the volumes of excreted urine were measured using a metabolic cage. The curves showing the variation of these parameters in each group were drawn.An automated chemistry analyzer  was used to assess the triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), pyruvate, and C-peptide levels in the plasma of rats. The serum insulin level was detected by ELISA.μm sections and stained with periodic acid-silver (PAS) for the detection of histopathological alterations and glycogen changes [Upon removal, the liver and skeletal muscles of each rat were immediately fixed in 4% formaldehyde. After routine paraffin embedding, the sample was cut into 5  changes .The rat livers collected at the end of the experiment were centrifuged, and changes in the superoxide dismutase (SOD), malondialdehyde (MDA), glutathione (GSH), glutathione peroxidase (GSH-Px), and catalase (CAT) levels were detected in the supernatant using the appropriate kits .Trichosanthes extracts was determined by micro method, using the appropriate kits. The removal rates of hydroxyl radicals , superoxide anion radicals , and DPPH radicals  were assessed.The in vitro antioxidant activity of the U test. Differences were considered to be statistically significant and very significant at ∗p <0.05 (∗/#) and ∗p <0.01 (∗∗/##), respectively.All of the quantitative data presented in this text were expressed as mean ± SD. A software was used (GraphPad Prism 8.0) for the statistical analysis, and variations among groups were assessed by one-way analysis of variance (ANOVA), followed by Dunnett's test. Meanwhile, nonparametric data were evaluated using the Mann–Whitney ∗∗p < 0.01 vs. the model group). Meanwhile, the weights of rats in the model group decreased gradually (##∗p <0.01 vs. the sham group), their blood glucose levels remained high, and their water consumption and urine volumes increased sharply . These symptoms are typical of type 1 diabetes. The body weights of rats in the water-soluble and ethanol fraction groups increased at the end of the experiment, and their blood glucose decreased to levels lower than the model standard level (16.5 mmol/L)  . TherefoTrichosanthes extracts on blood glucose regulation in diabetic rats, the OGTT experiment was performed. In this experiment, the blood glucose levels of rats were measured at 0, 30, 60, 120, 150, and 180 min after intragastric administration of 50% glucose solution. The results obtained showed that the sham group rats exhibited normal blood glucose levels after 180 min of glucose administration; however, the levels of the model group rats remained high. In the water-soluble fraction and ethanol fraction groups, the levels of blood glucose increased at first and then decreased to the normal level detected before the beginning of the experiment , which indicated that these extracts can effectively regulate the blood lipid metabolism in diabetic rats. Using the ELISA kit, the contents of C-peptide and insulin in rat serum were also detected, and the results indicated that STZ injection significantly decreased these contents in the model group rats .Compared to the sham group, the levels of TC, TG, and LDL-C in the model group were significantly higher, while those of HDL-C were significantly lower Figures . The lev Figures . This shTrichosanthes fraction increased the content of glycogen in the liver, but the ethanol fraction had no significant effect on this content. Moreover, both Trichosanthes extracts alleviated the skeletal muscle atrophy observed in diabetic rats (model group). However, only the ethanol extract increased the content of glycogen in rat skeletal muscles, compared to the model group (∗∗p < 0.01 vs. the model group). It should be noted that the liver and skeletal muscle glycogen contents detected using PAS staining were similar to those measured using the kit . Although the administration of the water-soluble fraction inhibited the diabetes-induced decrease in SOD (∗p < 0.05 vs. the model group), treatment with the ethanol fraction had no appreciable effect on the SOD content in rat livers (#p <0.05 vs. the sham group), and both Trichosanthes extracts decreased this level (∗p < 0.05 vs. the model group). The liver catalase content in the sham group was very high, but it was significantly reduced in the model group. Although the water-soluble fraction countered the effect of diabetes on the catalase content, the ethanol fraction did not appreciably change it . Finally, the GSH and GSH-Px levels in the livers of the model group rats were significantly less than those detected in the sham group rats , but the administration of the water-soluble or ethanol fractions obviously increased these levels.At the end of the experiment, the antioxidant activity of t livers . Moreovein vitro antioxidant activity of the Trichosanthes extracts in the livers of diabetic rats was tested using ascorbic acid as control. The results showed that this activity increases with increasing concentration of the extracts. However, in terms of hydroxyl and DDPH radical scavenging, the activity of the water-soluble fraction was greater than that of the ethanol fraction (Figures The  Figures . Meanwhi Figures .Trichosanthes can effectively and rapidly reduce the blood glucose levels in diabetic rats. Moreover, these fractions can regulate water consumption and urine excretion in T1DM rats, and long-term intervention also alleviates hyperglycemia symptoms. Although both extracts have a hypoglycemic effect, the underlying mechanisms are different. For instance, the water extract reduces systemic glucose concentration by regulating the glycogen content in the liver of diabetic rats, while the ethanol extract regulates the glycogen in the skeletal muscles. Moreover, the two Trichosanthes fractions have comparable antioxidant activities in vitro, but the activity of the water-soluble fraction is higher in vivo. This indicates that the antioxidant activity of the water extract is the main factor underlying the effect of this fraction in lowering blood glucose, regulating oxidative stress, and relieving diabetes symptoms [in vivo antioxidant activity. Therefore, the hypoglycemic effect of the ethanol extract is controlled by factors other than antioxidant activity.The experimental results obtained in this study indicate that both the water-soluble and ethanol fractions of symptoms , 21. Altβ cells [The main targets of hypoglycemic action are the liver, muscles, lipids, and islet β cells –24. The β cells , 26. HerTrichosanthes can both reduce the level of blood glucose in diabetic rats; however, the mechanisms underlying the hypoglycemic effects of these two extracts are not the same. This study did not explore the mechanism of the two extracts on inhibiting T1DM. But in later experiments, we will explore the mechanism of two extracts how to control the blood glucose changes in T1DM and find the targets of two extracts on inhibiting T1DM by metabonomics. In fact, we have started this work, and we will continue to show our research results in the future.This study shows that the water-soluble and ethanol extracts of


Our research objective was to determine which environmental and social factors were predictive of coronavirus disease 2019 (COVID-19) case and death rates in New York City (NYC), the original epicenter of the pandemic in the US, and any differential impacts among the boroughs. Data from various sources on the demographic, health, and environmental characteristics for NYC zip codes, neighborhoods, and boroughs were analyzed along with NYC government’s reported case and death rates by zip code. At the time of analysis, the Bronx had the highest COVID-19 case and death rates, while Manhattan had the lowest rates. Significant predictors of a higher COVID-19 case rate were determined to be proportion of residents aged 65 years plus; proportion of residents under 65 years with a disability; proportion of White residents; proportion of residents without health insurance; number of grocery stores; and a higher ozone level. For COVID-19 death rates, predictors include proportion of residents aged 65 years plus; proportion of residents who are not US citizens; proportion on food stamps; proportion of White residents; proportion of residents under 65 years without health insurance; and a higher level of ozone. Results across boroughs were mixed, which highlights the unique demographic, socioeconomic, and community characteristics of each borough. To reduce COVID-19 inequities, it is vital that the NYC government center the environmental and social determinants of health in policies and community-engaged interventions adapted to each borough. Approximately 19 months into the coronavirus disease 2019 (COVID-19) ongoing pandemic, the death toll amounts to approximately 607,000 individuals in the United States (US) alone and 4.26 million individuals globally . In addiSimilarly, recent data from the Centers for Disease Control and Prevention (CDC) demonstrate a consistent pattern of racial/ethnic differences in the risk for COVID-19 infection, hospitalization, and death  5,6,7].,6,7.5,6,Social determinants of health (SDH) have been conceptualized as the drivers of health for decades by many public health experts and are often at the root of health inequities. COVID-19 has brought to light many of these long-existing inequities . Race anAdopting the SDH framework, the study seeks to examine which environmental and social factors were most predictive of COVID-19 case and death rates in New York City (NYC), the original epicenter of the pandemic in the US, and any differential impacts among the boroughs. The first case relating to the COVID-19 pandemic in the United States was confirmed in NYC on 29 February 2020 ,11). SinPhysical distancing measures, which are necessary to prevent the spread of COVID-19, are substantially more difficult for those with adverse social determinants, contributing to higher rates of COVID-19 morbidity and mortality. As Yancy CW states, “social distancing is a privilege” that is simply not accessible in some communities, and the ability to isolate in one’s home and have full digital access to technology and the Internet are components of that privilege . People Individuals living in these adverse living and working conditions are more likely to experience underlying medical conditions, such as asthma and obesity, which in turn, places them at higher risk for severe cases of COVID-19 . For exaEnvironmental injustice is experienced through heightened exposure to air pollution and associated health risks, limited access to adequate environmental services , and loss of land or resource rights . A key dOn average, members of ethnically/racially diverse populations comprise 56% of the population living in neighborhoods with Toxic Release Inventory (TRI) facilities in place  compared to 30% elsewhere . Such faSpecifically, for asthma, a link between air pollutants and SARS-CoV-2 is considered to create a “double-hit” to the lungs leading to acute lung injury by attenuating tissue remodeling and influencing local inflammatory response . In a reIn another study, based on spatial data from the Bronx in NYC, a concentrated urban environment, Maantay (2007) found that air pollutants led to high asthma hospitalization rates, which particularly affected members of ethnic/racial minority groups and those living in poverty . IndividWe analyzed secondary data on various demographic, health, and environmental characteristics for NYC zip codes, neighborhoods, and boroughs along with the NYC government’s reported case and death rates by zip code (see details below). The New York City Health Department provided data on the COVID-19 case and death rates by zip code, each of which belongs to one of five boroughs: the Bronx, Brooklyn, Manhattan, Queens, and Staten Island (City of New York 2020a) . The StaValues were listed per neighborhood, which encompassed certain zip codes. Five zip codes used in NYC’s COVID-19 data were not listed in this portal , therefore, we assigned them to appropriate neighborhoods. The United States Census Bureau (2019) supplied data for percent of residents under 65 years old who have a disability . The Unir = ±0.8 or more extreme or slightly less if an exception to reduce confounding. For all correlation tests with either response variable COVID-19 case rate or COVID-19 death rate, strong correlations were considered to have an r value of ±0.75 or more extreme. Multiple regressions analyses were used to predict NYC COVID-19 case rate and COVID-19 death rate, non-stratified and stratified by borough. Pearson correlation was used to measure the correlation between all variables . ExplanaThe significance levels α = 0.05 and α = 0.10 were noted for correlation tests, while the significance level α = 0.10 was used for the regression analysis. Given that this was an exploratory study guided by the social determinants of health framework, we wanted to examine the potential variables that may have influenced the case and death rate in a comprehensive manner. All assumptions were reasonably met for every test and all analyses were completed with the use of RStudio . Maps wer = ±0.75 or more extreme.Based on r = 0.817), percent without a high school diploma (r = 0.728), and adult asthma ER visits (r = 0.826), leading us to exclude percent in poverty from the regression analysis due to confounding. Because fine particulate matter level and ozone level were highly correlated (r = −0.881), we chose to remove fine particulate matter level for the regression analysis. Because ozone level and mobility index were highly correlated (r = 0.747), and mobility index was also a similar measurement to percent decrease transit that would cause singularity issues in later regression models, we also chose to remove mobility index from subsequent regression models, even though the correlation coefficient did not reach our threshold of 0.8. Median household income, percent on food stamps, and percent without a high school diploma were also highly correlated with one another, so we chose to run separate regressions, one with each of the three variables as well as the rest of the explanatory variables to select the best fit model.The variable percent in poverty was highly correlated with a few explanatory variables, such as percent on food stamps (R-squared and lowest Akaike's Information Criteria(AIC) and Bayesian Information Criteria (BIC), leading us to choose the model with percent on food stamps as the best fit to predict COVID-19 case rate.p-value less than 0.001. Approximately 65.65% of the variability in the model is explained by the factors included. Significant predictors of NYC COVID-19 case rate include percent 65+, percent White, ozone level, number of grocery stores, percent Disability, and percent without health insurance.The overall model was significant, with a p < 0.001). Percent 65+ and percent non-US citizen were statistically significant variables in predicting the COVID-19 case rate of this borough. For Manhattan, approximately 67.84% of the variability in the model is explained by the factors included, and the model was significant (p = 0.0682), and approximately 72.09% of the variability in the model is explained by the factors included.In the Staten Island model, none of the individual explanatory variables were significant. The model overall was significant (p = 0.0764), but only approximately 29.91% of the variability in the model is explained by the factors included. Significant predictors for the Bronx model include percent White and percent on food stamps.The Bronx model was significant (p < 0.001). The significant variables are percent White, percent non-US citizen, ozone level, adult asthma ER visits, percent obese, and percent overcrowding.In the Queens model, approximately 58.8% of the variability in the model is explained by the factors included, and the model was significant (p < 0.001), and approximately 71.77% of the variability in the model was explained by the factors included.For Brooklyn, percent on food stamps, ozone level, adult asthma ER visits, percent obese, and percent overcrowding significantly predicted the borough’s COVID-19 case rate. The model was significant , and approximately 64.33% of the variability in the model is explained by the factors included.For Manhattan, percent 65+, percent non-US citizen, and adult asthma ER visits were significant predictors of the COVID-19 death rate in that borough. The model was significant (p = 0.045), and approximately 77.79% of the variability in the model is explained by the included factors.The only significant predictor for Staten Island was percent obese. For this borough, the model was also significant (p = 0.1038). Approximately 26.14% of the variability in this model is explained by the included factors. The variables percent White and ozone level were significant predictors for the Bronx’s COVID-19 death rate. The Bronx model was not significant (p < 0.001), and approximately 46.63% of the variability in the model is explained by the factors included. Percent 65+, percent non-US citizen, percent on food stamps, ozone level, and adult asthma ER visits were all significant predictors of the borough’s COVID-19 death rate. The model for Queens was significant (p < 0.001), and approximately 83.15% of the variability in the model is explained by the included factors. The significant predictors of Brooklyn’s COVID-19 death rate were percent 65+, percent on food stamps, and percent overcrowding.For the Brooklyn borough, the model was also significant overall , which considers “dwelling units occupied by more than one person per room as crowded” .There were no significant variables for the Staten Island case rate model, and only one variable (proportion of obese residents) was significant in predicting COVID-19 death rates, which suggests that other factors not included in our study and unique to Staten Island should be examined. Surprisingly, based on the non-stratified COVID-19 case and death rate models, a higher proportion of residents without health insurance predicted lower case and death rates. One explanation may be the accessibility of COVID-19 testing. It is worth noting that according to the NYC COVID-19 Citywide Information Portal , one is Collectively, our results can be interpreted in light of the environmental and social determinants that drive observed COVID-19 outcomes in NYC and in specific boroughs. Higher COVID-19 case and death rates in the Bronx points to inequities in terms of a disproportionate number of people who are living and working in contexts of higher risk . It is, therefore, important to understand the patterns of poverty level, racial/ethnic residential composition, education, air quality, and other relevant environmental and social determinants of health in each borough for the local and federal governments to figure out how and where to allocate more resources and craft policies to mitigate the worse COVID-19 case and death outcomes.When studying COVID-19, especially in the US, where information is continuously being updated, there are a few limitations. It is difficult to measure human behaviors such as individuals not following safety guidelines—whether due to the lack of knowledge at the beginning of the outbreak, the assortment of conspiracy theories, or other reasons—that may be influencing the case and death rates. Other limitations include not having a measurement for the reliability of test results, taking into consideration false positives and negatives, as well as not being able to factor in the general accessibility of getting tested. Despite these limitations, the study contributes to the literature on the importance of implementing an approach that takes into account and addresses the social and physical determinants of health to mitigate COVID-19 outcomes. Future research studies should analyze which of NYC actions were actually successful or harmful in addressing the COVID-19 pandemic. Studies are also needed to investigate the short-term and long-term effects of COVID-19 on health and how differential outcomes can be reduced in anticipation of subsequent waves of cases, as new variants of the virus emerge. Study results demonstrate that addressing the environmental and social determinants of health must be an essential part of a comprehensive response to the COVID-19 pandemic. The higher rates of morbidity and mortality for COVID-19 observed among racial/ethnic minority populations are, in large part, a product of the physical conditions in which individuals live and work.Public policies have the power to enhance health and also exacerbate COVID-19 inequities. With these analyses, we aimed to shed light on the related underlying environmental and social determinants of health related to COVID-19 case and death rates as well as how the local government can focus its COVID-19 response efforts towards the most impactful factors in order to reduce the case and death rates in the city and its boroughs. Going forward, the New York City government should focus on reducing health inequities, including COVID-19 inequities, by putting efforts towards centering the environmental and social determinants of health in policies  and comm


Controlling antibiotic resistance genes (ARGs) is a worldwide intervention to ensure global health. Hospital wastewater is the main pollution source of antibiotic-resistant bacteria and ARGs in the environment. Expanding our knowledge on the bacterial composition of hospital wastewater could help us to control infections in hospitals and decrease pathogen release into the environment. In this study, a high-throughput sequencing-based metagenomic approach was applied to investigate the community composition of bacteria and ARGs in untreated wastewater from three different types of hospitals . In total, 130 phyla and 2,554 genera were identified from the microbiota of the wastewaters, with significantly different bacterial community compositions among the three hospitals. Total ARG analysis using the Antibiotic Resistance Genes Database (ARDB) and Comprehensive Antibiotic Resistance Database (CARD) revealed that the microbiota in the wastewaters from the three hospitals harbored different types and percentage of ARGs, and their composition was specific to the hospital type based on the correlation analysis between species and ARG abundance, some ARGs contributed to different bacterial genera with various relationships in different hospitals. In summary, our findings demonstrated a widespread occurrence of ARGs and ARG-harboring microbiota in untreated wastewaters of different hospitals, suggesting that protection measures should be applied to prevent human infections. Concurrently, hospital wastewater should be treated more specifically for the removal of pathogens before its discharge into the urban sewage system. Antibiotic resistance poses a serious challenge to the treatment of pathogenic infections. However, antibiotic resistance genes (ARGs) are not only the outcome from human clinic settings, but it can also come from the interaction with animals, plants, soil, sea, and environmental samples. Two-thirds of antibiotics are consumed by animal husbandry , and somSome studies have shown a correlation between antibiotics, ARGs, and antibiotic-resistant bacteria in hospital wastewaters . There wIn this study, we evaluated the wastewaters of three hospitals affiliated with Southwest Medical University: Affiliated Hospital of Southwest Medical University (A group), Affiliated Hospital of TCM (B group), and Affiliated Hospital of Stomatology (C group). As drug usage and treatment regimens were dependent on the diseases being treated and the specialists at each hospital, the bacterial populations were expected to be affected, which would result in a significant difference in the prevalence of ARGs in the microbiome. Thus, we aimed to identify the bacterial community composition and prevalence of ARGs in the wastewaters from these three hospitals using high-throughput sequencing analysis. In addition, we attempted to determine special interventions for the protection against infections and the pretreatment of wastewater before its discharge into sewers, which may help reduce ARGs.From each hospital , 500ml wastewater was collected on October 12, 21, and 30, 2020, that is total nine samples were collected from the outflow of daily medical applications and stored in sterile 500ml glass bottles. Microbial samples from the wastewater were collected by filtration using filter membranes (0.2μm in diameter) and stored in sterilized centrifuge tubes at −80°C. Then, the filter membranes were sent to Majorbio Bio-Pharm Technology Co., Ltd.  for DNA extraction and Illumina HiSeq (pair-end library) sequencing.Total DNA was extracted from the triplet wastewater samples of the three groups using filter membranes with the MP Fast DNA™ Spin Kit for Soil according to the manufacturer’s instructions. The concentration of the extracted DNA was determined by spectrophotometry (TBS-380 followed by NanoDrop 2000). The DNA extract quality was assessed using 1% agarose gel electrophoresis.Genomic DNA was fragmented to 300bp (average size) using Covaris M220 , and a sequencing library was prepared using NEXTFLEX Rapid DNA-Seq Kit . Sequencing was performed using Illumina MiSeq  according to the manufacturer’s instructions. Sequence data associated with this project have been deposited in the National Center for Biotechnology Information (NCBI) Short Read Archive database (accession no. PRJNA723368).SeqPrep was used to merge paired reads from the 3' and 5' ends.Open reading frames (ORFs) from each assembled contig were predicted using MetaGene . Of thesWe clustered all predicted genes with 95% sequence identity (90% coverage) using CD-HIT . Among te-values ≤1e-5 using BLASTP , was used for annotating a cluster of orthologous groups of proteins  was used for KEGG annotation.e-value cutoff of 1e-5). The sequence identity was ≥90%, and the alignment length was ≥30 amino acids. Other analyses were performed using Cloud Majorbio.p<0.05 was considered statistically significant. A co-occurrence network was employed to visualize the correlation between antibiotic types and microbial taxa. A connection indicated a strong (ρ>0.5) and significant  Spearman’s correlation.The NCBI NR database was used to align the representative sequences of the NR gene catalog for taxonomic annotations, with parameter ins COG; . BLASTP In total, 847, 368, 612 clean reads were generated, with an average of 94, 152, 068 reads per sample. The statistical information of the contigs is listed in The bacterial community composition in the wastewaters was determined by the corresponding species and their taxonomic annotation information compared with the NCBI NR database. As shown in Acinetobacter (7.80–18.87%) in the A group, Streptococcus (6.98–13.78%) in the B group, and Arcobacter (14.28–47.90%) in the C group.In total, 130 phyla and 2,554 genera were identified from the microbiota of the wastewaters. When comparing the community abundance of bacteria at the phylum level in the wastewaters of the different hospitals, Proteobacteria was the dominant phylum in the C group (89.35–90.03%), while the A and B groups exhibited a relatively low abundance of this phylum . For the B group, Firmicutes were the most abundant phylum (49.58–53.44%), while the abundance of this phylum was low in both A and C groups . When evaluating data at the genus level, the composition of the microbiota was also different between the three groups . The mosThere was a significant difference at the phylum and genus levels between the hospitals. Samples from the A and B groups were from general hospitals that treated similar diseases but used different therapeutic regimens and drugs. Thus, these factors resulted in similar bacteria in the wastewaters but significantly different community compositions. Moreover, comparing samples from the A and B groups with the ones from the C group, a significant difference in community composition was observed. The C group hospital specializes in oral diseases, and the pharmaceuticals used for treatments here led to a less diverse bacterial community in the wastewater compared with the bacterial communities of the two general hospitals.p<0.05; p<0.05; Bacteroides was not statistically significant. Notably, the composition of Bacteroides in the samples from all three hospitals was different, contributing 24.05% of the total microbiome in the A group, 15.43% in the B group, and 6.86% in the C group. According to the cluster tree analysis . Among the antibiotic-relevant resistant genes, the three most abundant ARGs were associated with bacitracin, tetracycline, and tobramycin. The pairwise comparison of the three most abundant ARGs indicated differences between each two hospitals (p<0.01). There were no significant differences in the abundance of tetracycline resistance genes among the samples from the three hospitals. The percentage of ARGs associated with tobramycin differed between the A and C groups, while no significant difference was observed between the A and B or B and C groups.To verify the community prevalence of general ARGs in hospital wastewater, we used the Kruskal-Wallis H test to analyze the composition of general ARGs. Of the 15 main composition types of ARGs, six types differed in the wastewaters of the three groups ; p<0.05.ospitals –F, with The community abundance of bacterial comprehensive antibiotic resistance genes in the wastewater analyzed with CARD differed between the three groups . The perp<0.05). The differences in comprehensive antibiotic resistance genes for each of the pairwise comparisons at AR, AS, and AT class are shown in An in-depth analysis of the various class types was analyzed using the Kruskal-Wallis H test. As shown in Aeromonas contribute 14.50% for tetracycli ARG in C hospital wastewater, while Enterococcus, Bacteroides, Streptococcus, and Acinetobacter provided tetracycli ARG with different relative contributions in A and B groups. For bacitracin ARG, several types of bacteria were correlated with different relative abundances, while Arcobacter contributed with 47.49% in the C group hospital. Enterococcus contributed more than 50% for the tobramycin and sisomicin ARG type in B and C groups, while it contributed 12.80 and 13.31% for tobramycin and sisomicin ARG types in A and B groups, respectively; and they were both only 0.85% in C group. These results indicated that to reduce one type of ARGs in hospital wastewater, different types of bacterial species should be considered.The possible correlation between ARG types and bacterial genera was assessed under antibiotic type level. As shown in Acinetobacter was the possible host positively associated with six types of ARGs: amikacin, isepamicin, sulforamide, tobramycin, sisomicin, and netilmicin. Acidovorax was positively correlated with seven types of ARGs: amikacin, tobramycin, sulfonamide, netilmicin, sisomicin, dibekacin, and isepamicin. In addition, there were positive correlations between six ARGs types and Bacteroides. Enterococcus and Streptococcus were found to be host of tetracycline and macrolide ARGs.Then, a network analysis approach was applied to explore the correlation between ARG types and microbial taxa on antibiotic type level . There wArcobacter, Acinetobacter, and Dechloromonas phyla were predominant with different relative abundances  can be found at: CS conceived and designed the experiments. NT collected and processed the samples from the hospital wastewater system. CS and XG analyzed the metagenomics sequence data, created the figures, and wrote the manuscript. HL and LL helped to plan the project and contributed to development of the manuscript. QF and QZ assisted with sample collection and DNA extraction. 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.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.


Cardiovascular disease and cancer have increased the risk of mortality and morbidity in elderly persons worldwide. The aim of this study was to investigate the association of sedentary behavior and self-rated health with cardiovascular disease or cancer in elderly people. The data of 6785 elderly persons aged above 65 years from the Korea National Health and Nutrition Examination Survey 2014–2018 were examined. Binary logistic regression analyses assessed the association of sedentary behavior, self-rated health, and other risk factors with cardiovascular disease or cancer. Prolonged sedentary behavior in elderly people was associated with a high risk for cardiovascular disease (odds ratio (OR): 1.28, 95% confidence interval (CI): 1.08–1.52). There was a high risk for cardiovascular disease  or cancer  in elderly people who had poor self-rated health. This study identified the association between prolonged sedentary behavior and cardiovascular disease, and between poor self-rated health and cancer. Since prolonged sedentary behavior is related to cardiovascular disease, efforts are needed to reduce sedentary behavior hours and maintain good self-rated health. The growing elderly population has led to the introduction of the concept of “healthy aging” and life support. Cardiovascular disease (CVD) and cancer have increased the risk of mortality and morbidity in elderly persons aged 65 years and above worldwide . HoweverSedentary behavior (SB) is an important contributing factor to chronic diseases and cancer . Long seWith the increasing elderly population worldwide, the prevalence of chronic diseases is also increasing, and their self-rated health (SRH) is getting worse . SRH varSB is one of the factors that affect SRH; studies from different countries have found an association between SB and SRH ,11. The n = 31,109) and participants with insufficient data on sedentary behavior (n = 1304) or SRH (n = 836). As a result, 6785 participants were included in this study. This study was approved by the KCDC Institutional Review Board . The KNHANES was implemented without an IRB review in 2015–2017, according to the Bioethics Act and Enforcement Rules.The Korea National Health and Nutrition Examination Survey (KNHANES) is an annual survey program that was initiated in 1998 by the Korea Centers for Disease Control and Prevention (KCDC) to monitor the lifestyle of people. KNHANES collects data on smoking, physical activity, diseases or medical conditions, and the nutritional status of the general population of South Korea. This study utilized the data of the KNHANES 2014–2018 participants who were above 65 years old. Among 39,199 participants, we excluded participants aged <65 years  or poor . The outcome variable was the prevalence of CVD and cancer. CVD was defined as stroke, myocardial infarction, and angina. The types of cancers included stomach, liver, colon, breast, cervix, lung, thyroid, and other cancers. The presence of a CVD or cancer was assessed by asking the participants whether the diseases were diagnosed by a physician and whether they were receiving curative or preventive medication for the disease.The covariates that were assessed for socioeconomic status (SES) included sex, age , education level (middle school or lower/high school or higher), household income (discretized based on quintiles), marital status ( “yes” (married) or “no” ), physical activity, waist circumference, current smoking, high-risk alcohol consumption, and chronic diseases . Physical activity level was evaluated using the Global Physical Activity Questionnaire (GPAQ) Korean version , which wp-value of < 0.05 was defined as statistically significant. All analyses were performed using SAS version 9.4 . The participants’ characteristics were analyzed using the chi-square test. A binary logistic regression analysis was performed to analyze the association between SB, SRH, and risk factors and CVD or cancer; the results are expressed as odds ratios (ORs) and 95% confidence intervals (CIs). The combined effect of SB and SRH on CVD and cancer, stratified by sex, was also examined in a binary logistic regression analysis after adjustment for age, household income, education level, marital status, physical activity, current smoking, high-risk alcohol consumption, waist circumference, diabetes mellitus, hypertension, and dyslipidemia. A p < 0.01) and 420 (10.1%) had cancer. A total of 818 (23.0%) participants with CVD had a poor SRH and 552 (10.3%) participants with cancer had a poor SRH (p < 0.001). Of those with CVD, 419 (15.2%) participants were obese, 268 (17.9%) had diabetes mellitus, 660 (15.5%) had hypertension, and 362 (15.1%) had dyslipidemia. Of those with cancer, 440 (8.9%) individuals had a low educational level, 408 (10.5%) were obese, and 389 (9.2%) had hypertension (p < 0.05)  .In this study, the association of SB and SRH with CVD and cancer in Korean elderly persons aged 65 or above using the KNHANES data was examined. CVD was associated with SB and SRH, while cancer was associated with self-rated health. These results suggest that older adults need to reduce SB hours to prevent CVD and strive to maintain a good SRH. Previous cross-sectional studies of elderly English and Latin American adults found that elderly people with long SB hours seemed to have a poor SRH ,19. MoreThe risk for cancer was higher among the older adults with a poor SRH than those with a good SRH. Men had a higher risk for cancer than women, which was consistent with the results of a previous study. Ryou et al. reported that elderly men with a poor SHR had a higher risk for cancer than elderly women . In thisThe associations of CVD and cancer with SB and SRH were analyzed by sex, respectively. Older adults with short SB hours and a poor SRH had a higher risk for CVD than the elderly with short SB hours and a good SRH. The risk for CVD was 2.36 times higher for men and 1.49 times higher for women, but the difference was not significant. In addition, the elderly with prolonged SB and a poor SRH had a higher risk for CVD in both sexes than the reference group. Another cross-sectional study that included 7660 participants from Britain reported that the type of SB varies with the domain. For example, television viewing was associated with a higher risk for obesity and CVD than working while sitting; therefore, the risk for CVD also varies with the purpose for SB . MoreoveOlder adults with short SB hours and a poor SRH had a higher risk for cancer than the elderly with short SB hours and a good SRH. Women had a 2.06-fold higher risk for cancer; this risk was not significant among men. All elderly women with a poor SRH, irrespective of whether they have long or short SB hours have a higher risk for cancer, and the indicators of SRH are important risk factors for disease . Some stThis study has some limitations that should be considered. The data in this study were collected using a self-administered questionnaire; therefore, reporting errors or unsatisfactory answers are likely. However, the questionnaire used in the KNHANES was a verified survey tool, and the missing data of outcomes and main variables were deleted. The KNHANES was a cross-sectional survey. Therefore, through this study, it is impossible to establish a causal relationship of SB and SRH with CVD or cancer. In this study, the exact mechanism of the relationship between variables when combined (such as SB and SRH with cancer) is contrary to previous studies that showed a significant association of SB and SRH with cancer ,32; thisHowever, this study was able to find the association of SB and SRH with CVD or cancer using a structured questionnaire survey that was conducted in Korea; CVD and cancer are the major causes of mortality in elderly Koreans. The results of this study can be used as evidence in the development of public health policies for elderly people. This study examined the association of sedentary behavior and self-rated health with CVD or cancer among the elderly in Korea. This study suggests that there is a need to reduce elderly people’s SB hours; that is, elderly people have to avoid spending most of their time sitting or lying down because reducing SB hours can positively improve SRH. Therefore, future research is necessary to investigate the underlying reasons for long sitting and lying down time in the elderly. Additionally, policymakers need to focus more on education and health promotion among elderly adults for CVD and cancer prevention and the promotion of healthy aging.