Serpin is a superfamily of serine proteinase inhibitors. They have anticoagulative activities and immunoregulatory effects. The family has been widely studied in stroke patients and animal stroke models. However, results from clinical and preclinical studies are controversial. The systematic review and meta‐analysis aimed to determine whether serpin activities are affected by stroke and whether members of the serpin family could be used in stroke treatment.Literature was systematically searched in six databases until September 5, 2022. In the included studies, 47 clinical studies (8276 subjects) reported concentrations of serpin proteins in stroke patients and healthy controls. In total, 41 preclinical studies  reported neurological outcomes in animal models with serpin treatment and vehicle.Meta‐analysis of clinical studies showed that both ischemic (IS) and hemorrhagic stroke patients had higher thrombin‐antithrombin complex (TAT) levels and lower antithrombin (AT) levels which were persistent in the acute and subacute phase of IS. Meta‐analysis of preclinical studies reported the efficacy of serpins in treating stroke. C1‐INH and FUT175 reduced brain infarct size and improved sensorimotor and motor behavior in a dose‐ and time‐dependent manner in the MCAO models.Our study confirmed the important roles serpin family proteins played in the onset, progression, and treatment of stroke. Among serpins, AT and TAT may be used as blood biomarkers in the early diagnosis of stroke. C1‐INH and FUT175 could be potential medications for IS. The human serpin antithrombin and its complex with thrombin, in combination with other circulating factors, are novel blood biomarkers in the early diagnosis of stroke. Preclinical studies have consolidated the therapeutic effects of C1‐INH and FUT175 in treating ischemic stroke, which act in a dose‐ and time‐dependent manner. It ranks fifth among all causes of death.Serpin is a superfamily of serine proteinase inhibitors with typical primary structure.Serpin family proteins share substrates in the anticoagulative/inflammatory system but may behave differently in stroke. The anticoagulative and anti‐inflammatory activities of serpin proteins make them potential markers/regulators in the diagnosis/treatment of stroke. However, clinical studies reported altered serpin levels in stroke patients with controversial results. Meanwhile, preclinical studies have tested serpin as a treatment for stroke using animal models. This systematic review and meta‐analysis aim at summarizing evidence on serpin and stroke to investigate (1) if serpin proteins act as blood biomarkers of stroke and (2) if serpin proteins have therapeutic effects on stroke.22.1This systematic review and meta‐analysis were registered on PROSPERO for clinical studies CRD42021268081) and preclinical studies (CRD42021268063). It has followed the guides to systematically identify all relevant animal studies268081 an2.2In clinical studies, stroke was categorized into IS, HS, and transient ischemic attack (TIA). IS had five major subtypes according to the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) classification system, including the large artery disease, the cardiac embolism, the small‐vessel occlusion (lacunar), the stroke of undetermined etiology (cryptogenic) and the stroke of other determined etiology.In preclinical studies, animal models of IS included the middle cerebral artery occlusion (MCAO), hypoxic–ischemic (HI), and photothrombosis. The MCAO model, which was most widely used, could be further divided into transient (tMACO) and permanent type (pMCAO) depending on the duration of occlusion. Animal models of HS included SAH and ICH.2.3In full‐text screening, potentially eligible studies were split into clinical studies and preclinical studies. They were screened separately according to the inclusion and exclusion criteria. To prevent bias, inclusion criteria of clinical studies were pre‐specified as follows: (1) population: patients with stroke  and no comorbidity with other diseases; (2) intervention: no treatment; (3) control: healthy people without intervention; (4) outcome: concentrations of serpin proteins in the blood/serum/plasma tested by ELISA or relative RNA levels of serpins tested by real‐time quantitative PCR. Pre‐specified exclusion criteria were: (1) patients with no stroke, stroke patients with co‐morbidities; (2) case studies, cross‐over studies, studies without a separate control group; (3) stroke patients who had received treatment; (4) no control group as healthy people; (5) no outcomes of serpin levels.For preclinical studies, pre‐specified inclusion criteria were: (1) population: animal models of stroke , in controlled studies with one or more separate control groups; (2) intervention: administration of serpin, including all serpin family proteins and all administration routes; (3) control: vehicle ; (4) outcome: neurological outcomes such as brain infarct size and behavioral scores/tests. Pre‐specified exclusion criteria were: (1) no animal models, animals with co‐morbidities, in silico models; (2) case studies, cross‐over studies, studies without a separate control group; (3) studies with no serpin treatment, studies with combined treatment of serpin and tPA; (4) no vehicle group as control; (5) no neurological outcomes.2.4In clinical studies, data were extracted as (1) study characteristics, including author name, year published, and study design; (2) participant characteristics, including the number of participants, mean age, gender, and type of disease; (3) outcomes, including the serpin concentrations in protein level and mRNA level.3 or %) measured by 2,3,5‐Triphenyltetrazolium chloride (TTC) staining and other immunohistochemical methods and (ii) behavioral scores  and motor and sensorimotor performance measured by behavioral tests .In preclinical studies, the following data were extracted: (1) study characteristics; (2) subject characteristics, including the number of animals, species, age, gender, weight, and type of model; (3) intervention, including the type of serpin, dosage, injection method, and timepoint; (4) two continuous outcomes, including the mean and variance of (i) infarct size  by two authors independently.2.5Risk of bias assessment was performed according to the Cochrane RoB tool for clinical studies2.6g) was used as the measure of effect size.Q and reported as I2.Stata/IC 17.0 (StataCorp) was used to perform the meta‐analysis. An adjusted standardized mean difference , subacute phase (7 days–6 months), and chronic phase (>6 months). Outcomes reported at the first timepoint in each phase were used in the analysis.Q. A recommended significance level of 0.1 (#p < 0.1) was used instead of the more conservational level of 0.05.In preclinical studies, the overall effect on reducing brain infarct size was calculated for each serpin in three animal models of IS, including MCAO, HI, and photothrombosis. When more than one treatment group  and one control group were reported in a single study, each was considered as an independent experiment and the number of animals in the control group was split to avoid repeated comparison.2.7Funnel plot and Egger regression‐based test were used to analyze publication bias and small‐study effects.33.13.1.1n = 20), AT (n = 12), thrombin‐antithrombin complex , α1‐antitrypsin (n = 5), α1‐antichymotrypsin , vaspin , neuroserpin , the FVIIa‐antithrombin complex , and the pseudogene SERPINB9P1 (n = 1). 95% of studies had a low risk of bias in incomplete outcome data  and HS patients  while the TAT level was higher in both IS  and HS patients . In contrast, the PAI‐1 level was higher in ischemic conditions  and lower in HS patients . IS and HS patients had slightly higher levels of a1‐ACT and a1‐antitrypsin, the change of which were much milder as compared to TAT. IS patients had more neuroserpin  and less FVIIa‐AT  and vaspin . The long non‐coding RNA level of pseudogene SERPINB9P1 was reported as downregulated in IS patients in one study .The concentration of each serpin protein in stroke patients was compared to healthy people Figure . The blon = 1 or 2).In different phases of IS, the lower AT level and higher TAT level observed above were consistent from the acute phase (<7 days) to the subacute phase  and TAT , and the IS group of PAI‐1 , AT , and TAT . Leave‐one‐out analysis was performed to test the robustness of our findings. When a single study was removed, the overall effect of the remaining studies fell into the range of 95% CI of the original result , PAI‐1 (n = 6), PEDF , neuroserpin (n = 4), AT (n = 2), α1‐antitrypsin (n = 1), α1‐ACT (n = 1), LEX032 , PAI‐2 , two serpin artifacts including FUT175 (n = 7) and Aprotinin (n = 2), and one viral serpin CrmA  were reported  and FUT175 . Besides, C1‐INH reduced infarct size in the photothrombosis model as well . The high heterogeneity in studies of C1‐INH (I2 = 86%) and FUT175 (I2 = 73%) could arise from the variety of drug dosages and injection timepoints, which were further analyzed below.In total, 742 animals from 31 experiments were included in the overall analysis of serpin efficacy , PAI‐2 (p < 0.001), neuroserpin (p < 0.01), and LEX032 (p < 0.01), as reported in a small number of studies. Among them, PAI‐1 was reported effective in other ischemic models including HI  and photothrombosis . AT reduced the infarct size in MCAO animals by the effect size of −2.30 . As compared to AT, a1‐ACT, crmA, and aprotinin had relatively smaller effects. α1‐antitrypsin and PEDF had relatively larger effects but higher variance within the group.Similarly, the brain infarct size in animals with MCAO was reduced by PAI‐1 (3.2.3p < 0.01), 0.1 mg/kg  to 1 mg/kg  and 1 mg/kg  and improved behavioral scores  in the tMCAO model, but did not reduce infarct size in the pMCAO model . A high dose of 15U C1‐INH was effective in treating both tMCAO and pMCAO.In total, 431 animals from 32 experiments were included in the subgroup analysis of C1‐INH. The drug C1‐INH tested in the preclinical study was manufactured by CSL Behring, Baxter‐Immuno, and Pharming. In the tMCAO model, administration of 1–5U C1‐INH improved the composite behavioral scores  and 15U (I2 = 69%) could arise from the variety of administration time. Therefore, we further investigated the dose‐dependent efficacy in each group with different C1‐INH injection timepoints. In 5 experiments from 2 studies, C1‐INH was administrated post 1 h of tMCAO. The effect size of infarct size reduction was negatively correlated to dosage . No small‐study effect was observed in studies of FUT175 . When a single study was removed from the sensitivity analysis, the overall effect of the remaining studies fell into the range of 95% CI of the original result (Supplementary 9 in Appendix Publication bias was assessed using funnel plots (Supplementary 8 in Appendix 4p = 0.08). AT is the primary thrombin inhibitor in the human body that prevents blood coagulation. It regulates the activity of thrombin by forming the TAT complex in endothelial cell injury and the following thrombosis. TAT is the indicator of thrombin activation and is related to cardiovascular disease progression and poor outcomes. A previous meta‐analysis reported that the increased circulating TAT level was associated with subsequent stroke in patients with atrial fibrillation.The systematic review and meta‐analysis examined clinical and preclinical evidence of serpin family proteins in the pathogenesis and treatment of stroke. Clinical studies revealed that both IS and HS patients had decreased concentrations of AT and increased concentrations of TAT, which could act as diagnostic biomarkers. Consistently, preclinical results showed that AT effectively treated IS by reducing brain infarct size in animal models of MCAO (p = 0.12) while decreased in HS (p = 0.26). Previous studies have reported that PAI‐1 level was significantly higher in IS patients with lone AF and patients with atherothrombotic large artery disease.p = 0.23). In human body, α1‐antitrypsin reduces the inflammatory activity of protease enzyme elastase. The genetic polymorphism of α1‐antitrypsin may play a more important role in stroke. A common coding variant [M1 (A213V)] in α1‐antitrypsin is a risk factor for large artery stroke.A large number of studies in our meta‐analysis reported PAI‐1, which played a crucial role in the fibrinolytic system and has been recognized as the central hub in the pathogenesis and progression of thrombotic vascular diseases.−/− mice.In preclinical studies, our meta‐analysis summarized the therapeutic effects of C1‐INH, a human serpin, and FUT175, a synthetic serpin artifact. Both effectively reduced brain infarct size and improved motor/sensorimotor functions in animal models of MCAO. Functionally close to each other, C1‐INH and FUT175 are both complement inhibitors.There were some limitations in our meta‐analysis. The overall analysis of clinical studies showed high heterogeneity, especially in IS studies, which were discussed above. Besides, we could not relate the change of serpin proteins in stroke patients to their clinical outcomes. Because most studies included did not report the severity of stroke, such as the NIHSS score. Therefore, we could only relate serpin proteins to the progression of IS, which showed consistency of serpin involvement after IS onset. In our meta‐analysis of preclinical studies, there were limited data included in many serpin groups, such as AT. In turn, some serpin proteins which researchers have focused on in the preclinical area have not been investigated clinically, such as C1‐INH. Therefore, we call for more communication between the clinical and preclinical branches and more attention to the function and utility of serpin family proteins in stroke progression, diagnosis, and treatment.5The decreasing AT level and increasing TAT level could be used as blood biomarkers (maybe in combination with other circulating factors) in the clinical diagnosis of acute and subacute IS. Preclinical evidence supported that C1‐INH and FUT175 effectively reduced the brain infarct size and improved animal behavior by rescuing motor and sensorimotor functions in MCAO models, which showed their potential as therapeutic drugs for IS.BY, L Luo, L Li, ZW, and RC performed literature search, screening, and risk of bias assessment, and conducted data extraction. BY performed data analysis and drafted the manuscript. XX and YW conducted the study conception and design, revised the manuscript, and supervised the project. All authors read and approved the final manuscript.This work was supported by the National Key R&D Program of China (2021ZD0202805 and 2019YFA0709504), the National Natural Science Foundation of China (31900719), the Innovative Research Team of High‐level Local Universities in Shanghai, Science and Technology Committee Rising‐Star Program (19QA1401400), 111 Project (B18015), Shanghai Municipal Science and Technology Major Project (2018SHZDZX01), and Shanghai Center for Brain Science and Brain‐Inspired Technology.No conflicts of interest were disclosed.Appendix S1Click here for additional data file.Appendix S2Click here for additional data file.


To detect functional connectomes of akinetic‐rigid (AR) and tremor and compare their connection pattern.Resting‐state functional MRI data of 78 drug‐naïve PD patients were enrolled to construct connectomes of AR and tremor via connectome‐based predictive modeling (CPM). The connectomes were further validated with 17 drug‐naïve patients to verify their replication.The connectomes related to AR and tremor were identified via CPM method and successfully validated in the independent set. Additional regional‐based CPM demonstrated neither AR nor tremor could be simplified to functional changes within a single brain region. Computational lesion version of CPM revealed that parietal lobe and limbic system were the most important regions among AR‐related connectome, and motor strip and cerebellum were the most important regions among tremor‐related connectome. Comparing two connectomes found that the patterns of connection between them were largely distinct, with only four overlapped connections identified.AR and tremor were found to be associated with functional changes in multiple brain regions. Distinct connection patterns of AR‐related and tremor‐related connectomes suggest different neural mechanisms underlying the two symptoms. The akinetic‐rigid (AR) related and tremor‐related connectomes were detected from drug‐naïve Parkinson disease patients and further verified in an independent set. Comparing two connectomes found that the patterns of connection between them were largely distinct and only four overlapped connections identified. Distinct connection patterns of AR and tremor‐related connectomes reveal different neural mechanisms underlying two symptoms. Traditionally, motor symptoms were thought to be linked with dysfunction of the motor circuit, which connects the motor cortex to a particular territory within the basal ganglia nuclei.Resting‐state functional MRI (Rs‐fMRI) allows simultaneous investigation of different brain regions and is, therefore, suitable for detecting symptom‐related functional bases across the whole brain.The effects of the medication should also be taken into account when analyzing the relationship between functional connectomics and motor symptoms. It has been known that dopaminergic medicine regulates the functional activity of the circuits involved in motor processes,Therefore, this study sought to identify connectomes related to AR and tremor at the individual level among drug‐naive PD patients. The detected connectomes were then validated among an independent set of drug‐naive patients to verify their replication. As mentioned previously, the two symptoms are thought to link with different neural bases, thus connectomes of AR and tremor should be distinct. To verify this hypothesis, we then compare the connection patterns of these two connectomes. In addition, we compared connectome strength between patients and normal controls to determine further clinical relevance.22.1N = 3) and cognitive impairment based on the Mini‐Mental State Examination (MMSE) score (N = 3).A total of 87 drug‐naive patients were initially recruited. All patients provided written informed consent forms following the approval of the Medical Ethics Committee of our institution. Diagnosis of PD was made by a senior neurologist (B.R.Z.) according to the United Kingdom PD Society Brain Bank criteriaThe severity of symptoms was evaluated according to the Unified Parkinson's Disease Rating Scale part III (UPDRS III) for each patient. The akinetic‐rigid (AR) was evaluated by summarizing the rating on rigidity, finger tapping, hands movements, rapid alternating movements of hands, leg agility, arising from the chair and body bradykinesia, and the tremor was assessed as a sum of rating on resting tremor of the face, arms and legs, and action or postural tremor of the arms.2.22.2.1All imaging data, which included Rs‐fMRI and T1‐weighted sequences, were acquired from a 3.0 Tesla MRI scanner . The head of each participant was stabilized with foam pads, and earplugs were provided to reduce the noise during scanning. The parameters of the two sequences were detailed in Appendix 2.2.2Rs‐fMRI data processing was carried out using Statistical Parametric Mapping version 12 and Data Processing Assistant for Resting‐State fMRI.2.2.3r) were Fisher's r‐to‐z transformation to construct 268 × 268 matrices. Each value of the matrix represented the connection strength between all pairs of nodes.The whole‐brain functional connection matrix was constructed for each patient in the MNI space. Network nodes were defined using the 268‐ROI functional brain atlas.2.3The flowchart of connectomes construction and evaluation was shown in Figure 2.3.1N = 77) were enrolled for training. First, in the training set, the partial correlation analysis  between connection strength and symptoms severity  was performed  were selected and divided into positive (r > 0) and negative (r < 0) connections according to correlation coefficient.The CPM was used to detect connectomes related to two symptoms. Due to the small number of patients, leave‐one‐out‐cross‐validation was performed as internal validation during model construction.d Figure . ConnectA total of 78 iterations were performed until all patients had been left out at once. To reduce potential variation, only connections shared across every iteration  were retained in the connectomes. Each connectome was composed of positive network  and negative network . The network strength was determined by adding up the strength of all connections enrolled in it.2.3.2p values is overestimated, the 1000‐time permutation test was performed to further ensure the significance. In the permutation test, the behavior data and connection matrices were randomly shuffled by permuting patients' labels 1000 times and repeated CPM analysis with the shuffled data. Based on these null distributions, the p values of predictabilities were calculated (ppermu), and ppermu <0.05 was considered statistically significant.The significance of the detected connectome was quantified through Spearman correlation analysis between the observed and predicted severity because neither AR nor tremor severity was normally distributed. As the cross‐validation analyses of the leave‐out folds are not independent and thus the degree of freedom for parametric culated ppermu, an2.3.3p‐value for connection selection and applied atlas could influence the significance of the model  functional brain atlas. All nodes were divided into 11 macroscale brain regions based on anatomical labels, including the prefrontal lobe, motor strip, insula, parietal lobe, temporal lobe, occipital, limbic, cerebellum, thalamus, basal ganglia, and brainstem.z‐test.The following analyses were then conducted. First, to determine whether the underlying brain mechanisms to symptoms could be simplified to functional alternation within a single region, 11 region‐based models were constructed using nodes and connections within a single region. Second, to have a further understanding of the importance of each region for prediction, 11 lesioned models were constructed by excluding the nodes of one region and their corresponding connections. Regions that degrade original performance the most upon exclusion would then be assigned greater importance in the connectomics.2.4.2The connection patterns between AR and tremor connectomes were compared at the node, region, and connection levels. Comparing was conducted between two negative and two positive networks. Furthermore, a cross‐comparison was conducted between negative and positive networks.At the node and the region level, Pearson's correlation analysis was applied to determine whether the contributions of nodes/regions to AR‐ and tremor‐related connectomes were similar. Significantly higher correlation coefficients indicate greater similarity between connection patterns.p = 1‐hygecdf   and tremor‐dominant (TD) subtypes according to the ratio of mean tremor score to mean AR scores .2.6t‐test. Continuous variables with non‐normal distribution were presented as median and range and compared with the Mann–Whitney test. Differences between qualitative variables were compared with the Chi‐square test. A two‐sided p‐value <0.05 was considered significant unless mentioned.The clinical characteristics of all participants were analyzed by using SPSS software (Version 25). The Kolmogorov–Smirnov test was applied to identify the normal distribution of continuous variables. Continuous variables with normal distribution were presented as average ± standard deviation and compared with a two‐sample https://www.nitrc.org/projects/bioimagesuite/.Statistical analyses of connectomes construction and evaluation had been detailed in the corresponding parts mentioned above. All processes were performed in MATLAB  with custom scripts.33.1r = 0.28, ppermu = 0.018) and tremor   as well as predicted scores and head‐motion .Characteristics of enrolled 78 drug‐naïve patients were detailed in Table ) Figure . There wrmax = 0.31, ppermu <0.038) and tremor , demonstrating that head‐motion, threshold, or atlas did not influence the significance of prediction  as well as observed and predict tremor severity  and limbic system  while removing other regions did not significantly decrease the prediction of AR  and cerebellum  (Table None of the region‐based models could significantly predict two symptoms after the FDR correction Table . ResultsAR Table . As for 3) Table .3.4N = 44), and motor strip had the most positive connections of tremor‐related connectome (N = 63). The most negative connections of the AR‐related connectome come from the motor strip (N = 48), and the most negative connections of the tremor‐related connectome come from the temporal lobe (N = 90). Nodes with a sum of connections ranked in the top 5% (N = 12) were listed in Table Figure p = 0.001) between seven nodes overlapped . There was no significant correlation between AR positive network and the tremor negative network at either level. No common connections were detected in the cross‐comparison analysis.The cross‐comparison analysis of networks' connection patterns found a weak correlation between AR‐negative network and tremor‐positive network only at the node level (3.5p = 0.008) and milder tremor  than TDs, and no other characteristics were significantly different.Characteristics of ARDs, TDs, and NCs were detailed in Table p = 0.003) but comparable positive network strength  relative to NCs  to provide additional information on the underlying neural base. The primary findings detected in this study need to be validated with external data sets from other institutions.In conclusion, both AR and tremor should be viewed as connectome dysfunction. In addition to regions included in motor circuits, there were also regions controlling sensory, emotional, and cognitive processes that correlated with symptom severity. Connectomes related to two symptoms had distinct connection patterns, which to some extent reflect their different neural mechanisms.H.T.W., C.Z., and X.J.G. contributed to the conception and design of the study. H.T.W., Z.Y.C., X.Q.B., T.G., J.J.W., J.W.C., J.Q.W., C.Q.W., X.C.L., T.G., G.L.Y., and B.R.Z. contributed to the acquisition and analysis of data. H.T.W,C.Z., and X.JG contributed to manuscript drafting. Interpretation of the results, critical revision of the manuscript, and final version approval: all authors.The authors have declared that no conflict of interest statement.Appendix S1Click here for additional data file.


PCBP1, which was upregulated in long‐lived mammals but dramatically downregulated during aging in all splenic immune cell types. Supportively, immune cells of mouse spleens contained more free iron than those of bat spleens, suggesting higher level of ROS‐induced damage in mouse. PCBP1 downregulation during aging was also detected in hepatic but not pulmonary immune cells, which is consistent with the crucial roles of spleen and liver in organismal iron recycling. Furthermore, PCBP1 perturbation in immune cell lines would result in cellular iron dyshomeostasis and senescence. Finally, we identified two transcription factors that could regulate PCBP1 during aging. Together, our findings highlight the importance of iron homeostasis in splenic anti‐immunosenescence, and provide unique insight for improving human healthspan.Although immunosenescence may result in increased morbidity and mortality, many mammals have evolved effective immune coping strategies to extend their lifespans. Thus, the immune systems of long‐lived mammals present unique models to study healthy longevity. To identify the molecular clues of anti‐immunosenescence, we first built high‐quality reference genome for a long‐lived myotis bat, and then compared three long‐lived mammals  versus the short‐lived mammal, mouse, in splenic immune cells at single‐cell resolution. A close relationship between B:T cell ratio and immunosenescence was detected, as B:T cell ratio was much higher in mouse than long‐lived mammals and significantly increased during aging. Importantly, we identified several iron‐related genes that could resist immunosenescence changes, especially the iron chaperon,  To identify molecular clues of anti‐immunosenescence, we compare three long‐lived mammals versus the short‐lived mammal, mouse, in splenic immune cells at single‐cell resolution. We detect higher splenic B:T cell ratio and higher free iron level in mice, while higher expression levels of iron homeostasis‐related genes in long‐lived species. Our findings highlight the importance of iron homeostasis in splenic anti‐immunosenescence, and provide unique insight for improving human healthspan. BUSCObenchmarking universal single‐copy orthologsCistrome DBCcistrome Ddata BbrowserDEGsdifferentially expressed genesGOGgene OontologyHi‐C sequencinghigh‐throughput chromosome conformation capture sequencingKDknockdownKEGGKyoto Eencyclopedia of Ggenes and Ggenomes DdatabaseLIPlabile iron poolMbmegabaseN50length of the shortest contig for which longer and equal length contigs cover at least 50 % of the assemblyNCnegative controlNESnormalized enrichment scoreNK cellsnatural killer cellsNMRsnaked mole ratsROSreactive oxygen speciesscATAC‐seqsingle‐cell assay for transposase‐accessible chromatin sequencingscRNA‐seqsingle‐cell RNA sequencingSDstandard deviationshRNAshort hairpin RNAsiRNAsmall interfering RNATPMtranscripts per kilobase of exon model per million mapped readsUMAPuniform manifold approximation and projection1The immune system protects the organism by fighting infection, eliminating cancerous cells, and regulating tissue repair, etc., which is critical for the organismal homeostasis and longevity , NMR, and human) and the short‐lived mammal, mouse, at single‐cell resolution, and we aim to (i) uncover the similarities and differences in the cellular diversity and gene expression pattern of immune cells across these species; (ii) identify marker genes that are more highly expressed in long‐lived species, which may have anti‐immunosenescence potentials; (iii) and finally explore their roles in anti‐immunosenescence. In summary, the systematical comparison of splenic immune cells between long‐lived versus short‐lived mammals will provide novel insights in understanding the molecular mechanisms of anti‐immunosenescence and healthy longevity.As the largest secondary lymphoid organ of the body, the spleen plays a critical role in hematopoiesis and blood filtration  issued by Institute of Zoology, Guangdong Academy of Science. Two male and two female myotis bats were used for single‐cell RNA sequencing (scRNA‐seq), and four male myotis bats were used for LIP assay. Young  and aged  wild‐type C57BL/6J mice were purchased from Casgene Biotech CO., Ltd. All mice were housed under standard environment and provided with clean water and food ad libitum. The Administrative Panel on Laboratory Animal Care at the Guangzhou Laboratory approved all the experimental procedures in this study.https://www.R‐project.org/).Maximum longevity (years) and adult body mass (g) of mammals were downloaded from the AnAge database  with a scissor. Splenic immune cells were released by grinding the spleen fragments through a 100‐μm cell strainer with a syringe plunger, or pipetting gently with a Pasteur pipette. Cells were washed with RPMI 1640 with 10% FBS and centrifuged at 450 g for 5 min at 4°C, then resuspended with 3 mL ACK Lysing Buffer  for 5 min at room temperature to remove red blood cells. Cells were then washed twice and resuspended in PBS with 0.1% BSA, passed through a 40‐μm filter, counted and checked viability using trypan blue before use. The cells and the wash buffer should be kept on ice during the whole procedure to preserve cell viability.Animals were anesthetized by intraperitoneal injection of isoflurane, then the spleens were harvested and immediately transferred into 5 mL iced RPMI 1640 with 10% FBS, and then cut into small pieces , libraries were prepared using VAHTS RNA‐seq V3 Library Prep Kit for Illumina  following the manufacturer's instruction. Quality of both scRNA‐seq and bulk RNA‐seq libraries was evaluated by the Fragment Analyzer . Libraries were sequenced on an illumine NovaSeq6000 in the PE150 mode.2.4https://github.com/Nextomics/NextDenovo, NextDenovo v.2.3.1) was used to assemble the contigs with different seed depth, including 45X, 50X, and 55X. 50X seed depth was used based on the N50 length and total length of the assembly results. Third, NextPolish  was used to polish the contigs by using Illumina data with default parameters. Fourth, Juicer v.1.6  and Oxford Nanopore technologies long‐read sequencing (ONT RNA‐seq) on 13 tissues of adult male bats for genome annotation. These tissues included heart, liver, spleen, lung, kidney, intestine, cochlea, stomach, pancreas, muscle, brain, eye, and testis. Meanwhile, Illumina RNA‐seq data from NCBI, and well‐annotated protein sequence from human, mouse, and other bats were also collected for genome annotation. Briefly, genome annotation mainly included three steps: ab initio gene prediction, protein homology‐based and transcriptome‐based prediction.https://github.com/nanoporetech/pychopper) was used to trim ONT long reads and identify the full‐length cDNA reads. The identified full‐length reads were mapped to genome assembly using minimap2 v2.24 . SNAP v2013‐11‐ 529 and AUGUSTUS v3.2.3 were implemented to MAKER v2.31.11  were collected. Then we used EvidenceModeler v1.1.1 to integrate the above collected evidences into consensus gene models. The weights we used on the integration step were 12 for ONT‐evidence, 11 for PASA‐evidence, 10 for StringTie‐evidence, 9 for Trinity‐evidence, 5 for gth‐evidence, and 2 for marker‐evidence. Finally, alternative splicing models and UTRs were added to EVM‐models by using PASApipeline in “genome annotation” mode. The downstream inspection and function annotation were based on the resulted PASA‐models.http://transdecoder.github.io) were used to predict the putative peptides for PASA‐model and the results were aligned against to the Uniprot database by using blastp v2.10.0+ with E‐value below 1e‐6. Peptides with no hits and length below 100 amino acids were removed from the PASA‐models. BUSCO v4.1.4 with mammalian (odb10) dataset was used to evaluate the completeness of annotation , including Canis lupus familiaris, Felis catus, Bos taurus, Sus scrofa, Equus caballus, Homo sapiens, Macaca mulatta, Mus musculus, Rattus norvegicus, Pteropus vampyrus, and Myotis lucifugus. Other bat species proteomes, such as Phyllostomus discolor (GCF_004126475.2), Pipistrellus kuhlii (GCF_014108245.1), Rhinolophus ferrumequinum (GCF_004115265.1), Rousettus aegyptiacus (GCF_014176215.1), Molossus molossus (GCF_014108415.1), and Myotis myotis (GCF_014108235.1) were downloaded from NCBI. The proteomes of M. ricketti was generated by TransDecoder v.5.5.0 (https://github.com/TransDecoder/TransDecoder) based on the genomes we got. Second, we filtered the orthologous groups using the filter_groups.py file (available at https://zenodo.org/record/3786201) by setting the number of species to 16. Third, MAFFT v7.48 . Finally, the phylogenetic species tree was built using IQTREE v. 2.0.3 with LG model and was visualized by FigTree v1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/). The node supports of the phylogenetic tree was obtained by 1000 replicated of bootstrapping. Mus musculus was used as outgroup.OMA standalone v. 2.4.2 was used to identify the orthologous genes of target species  supplemented with 10% FBS and 1% penicillin–streptomycin. The mouse B cell line WEHI231 and human T cell line Jurkat were grew in RPMI 1640 supplemented with 10% FBS and 1% penicillin–streptomycin.Pcbp1 knockdown in Raw264.7, WEHI231 and Jurkat cell lines were established by transduction of shRNA lentivirus. Non‐target control (NC) and Pcbp1 shRNA sequence were cloned into pLVX‐shRNA2‐ZsGreen1‐Puro vector. Package of lentivirus was performed by transfecting shRNA vectors into 293T cells using Lipofectamine 3000 Reagent , 48 h after transfection, the supernatants containing lentivirus were collected and concentrated using 5 × Lentivirus Concentration Reagent , then stored in aliquots at −80°C before use.Transfection of siRNAs was preformed using Lipofectamine RNAiMAX Reagent  according to the manufacturer's instruction, cell samples were collected 48 h after transfection. For RT‐qPCR, total RNA from all cell lines, mouse and bat splenic immune cells were extracted using EZ‐press RNA Purification Kit . All cDNA was synthesized using HiScript III RT SuperMix for qPCR kit . qPCR was performed using ChamQ SYBR qPCR Master Mix  on Quantagene q225 system . All sequence of siRNA and RT‐qPCR primers were listed in Table 2.76 cells/ml in PBS with 0.1% BSA were incubated with 50 nM calcein‐AM  for 15 min at 37°C in the dark for free iron chelation. Cells were immediately analyzed on a flow cytometer (Agilent Novocyte Advanteon), the mean florescence intensity (MFI) was measured at the FITC channel. Followed by incubation of 100 μM SIH  at room temperature for 30 min, cells were analyzed again. Cellular LIP level was estimated as the MFI difference (△F).We first compared between bats and mice, where four male myotis bats and four mice were used for LIP assay. Then we compared between young and aged mice, where young  and aged  mice were fed with standard diet and high iron diet  for 4 weeks, respectively. LIP of the splenic immune cells was evaluated as described previously. For each sample, 1 × 10Pcbp1 knockdown immune cell lines were treated with different concentration of ferric citrate  for 4 days. Non‐heme iron concentrations were determined using the Iron assay kit  following the manufacturer's instruction. Ferric and ferrous iron levels were calculated from the standard curve and normalized to the protein content for each sample using BCA Protein Assay Kit .The NC and Pcbp1 shRNA knockdown groups were plated in 96‐well‐plate, 2500 cells/well. Cell viability was assayed using Cellcounting‐Lite 2.0 Luminescent Cell Viability Assay  following the manufacturer's instruction, cell proliferation ratio was calculated from Day 1 to Day 4.For cell viability assay, cells from both NC and Pcbp1 knockdown Raw264.7 cells were incubated in 10 ug/ml Zymosan A (S. cerevisiae) BioParticles conjugated with Alexa Fluor 594  for 3 h. After thorough washing, cells were visualized under a fluorescent microscope, then analyzed on a flow cytometer (Agilent Novocyte Advanteon) to detect the percentage of phagocytic cells.For phagocytosis assay, NC and 2.8scRNA‐seq fastq files were demultiplexed to their respective barcodes using the 10 Genomics Cell Ranger mkfastq utility. Unique molecular identifier (UMI) counts were generated for each barcode using the Cell Ranger (v5.0.1) count utility. The bat reference genome was generated by ourselves.CD79A and CD79B); T cells (CD3E and CD3G); macrophages (CD68 and CD86); neutrophils (S100A8 and IL1R2); NK cells, (KLRC1 and NKG7); Ltf‐high neutrophils: (CAMP and LTF), and erythroid cells (AHSP and TFRC). To identify differentially expressed genes between cell types across species, we used a negative binomial model as implemented in the Seurat ‘FindMarkers’ function, comparing each individual cell type to all other cells within the major cell type cluster . Genes were considered differentially expressed if the adjusted p value was lower than 0.05. The single‐cell dataset of young and aged mice spleen was compared to get the upregulated genes in the young mouse splenic immune cells. Then we defined the upregulated genes in the long‐lived species and in the young mice as candidate anti‐immunosenescene genes.Count data were processed with the Seurat package (v4.1.0). For quality control, genes that were expressed in fewer than three cells and cells that expressed fewer than 100 genes were excluded from analysis. Integration was performed using canonical correlation analysis (CCA), essentially according to the Standard Workflow protocol provided by the authors. The filtered gene‐barcode matrix was analyzed by PCA. Then Uniform Manifold Approximation and Projection (UMAP) was performed on the top 30 principal components for visualizing the cells. Meanwhile, graph‐based clustering was performed on the PCA‐reduced data for clustering analysis with Seurat. Clusters were identified by the expression of known cell‐type markers: B cells  using STAR . Fastq files were aligned to the mouse reference (mm10) and “cellranger‐atac count” function  was used to generate single‐cell accessibility counts.scATAC‐seq of CD45All downstream scATAC‐seq analysis was conducted by using ArchR  . We checked the expression pattern of Pcbp1 in different tissues at different ages based on data from the microfluidic droplet approach.Single‐cell datasets from human liver of different ages were download from Liver Cell Atlas (2.12Metascape was used to perform Gene ontology (GO) biological process enrichment analysis  of existing genome‐wide ChIP‐seq data were used to probe which transcription factors might regulate Pcbp1 in mouse. The half‐decay distance to transcription start site was set as 10 kb. Second, SCENIC was used to identify regulons based on genes co‐expression and DNA‐motif analysis , T cells (CD3E and CD3G), macrophages (CD68 and CD86), neutrophils (S100A8 and IL1R2), NK cells (KLRC1 and NKG7), Ltf‐high neutrophils (CAMP and LTF), and erythroid cells (AHSP and TFRC)  They should exhibit higher expression levels in all these three long‐lived species compared with mouse. Because if a certain gene is more highly expressed in only one long‐lived species, it may be due to species‐specific difference. However, if a certain gene exhibits higher expression level in all the three distantly related species: bat (chiroptera), NMR (rodentia), and human (primates) than mouse (rodentia), it is more likely to involve in the common phenotype of these three long‐lived species, namely, longevity, rather than species difference. (ii) The expression levels of candidate genes should significantly decrease during aging.PCBP1, SRSF4, SRSF9, NDFIP1, DOCK8, and RAC1), four genes for T cells , five genes for B cells , five genes for NK cells   Figure a,b.PCBP1 in all splenic immune cell types, ISCU in T and B cells, and PPP1CC in B and NK cells, indicating a universal anti‐immunosenescence role  to other proteins for storage, heme synthesis or implement different biological redox reactions  clusters, which regulate metabolism and iron homeostasis. Decreased ISCU expression can reduce the translation of the iron storage protein FTH1 and lead to iron accumulation in liver cancer  on cell membrane, and NDFIP1 deficiency increases ferroportin in hepatic macrophages and increase circulating iron , five genes for T cells , three genes for B cells , seven genes for NK cells   Figure d,e. Alth3.4As iron‐related genes were related to splenic anti‐immunosenescence, we performed iron experiments in splenic immune cells of myotis bats and mice. We measured free iron levels in the form of labile iron pool (LIP) in splenic immune cells by cell cytometry. Compared with bat splenic immune cells, mouse splenic immune cells contained much more free iron Figure . These rWe also measured free iron levels in splenic immune cells of young and aged mice, but detected no differences Figure . However3.5Pcbp1, Srsf4, Srsf9, Ndfip1, Dock8, and Rac1. As shown in Figure Ndfip1 , hemoglobin synthesis (Eif2ak1), and iron overload (B2m); and also upregulated genes related to iron storage , iron reduction (Cyb561a3), iron–sulfur cluster assembly (Ciao2b and Glrx3 and Bola2), cellular iron export (Slc40a1)  proteins  were not previously reported to be iron related, their knockdown also severely affected the iron homeostasis in the macrophage cell line , and human T cell line (Jurkat) also resulted in higher immunosenescence scores but lower anti‐immunosenescence scores   might regulate Pcbp1 , other genes that have not been previously reported to be iron related are also able to regulate iron homeostasis. For example, although there is no evidence that Srsf4, Srsf9, Dock8, and Rac1 are iron related, knocking down each of them severely affects the iron homeostasis in the macrophage cell line. Besides, we find that bat splenic immune cells contained less free iron but more protein bound iron than mouse splenic immune cells, indicating bat processes stronger ability to control oxidative stress induced by free iron, which may contribute to their longevity (Zeidan et al., Furthermore, we identify several iron‐related genes exhibiting prominent anti‐immunosenescence feature: higher expression in long‐lived species and decreased expression during aging. By cross‐species comparison and manually checking the expression patterns, a total of 20 candidate anti‐immunosenescence genes are identified in different splenic immune cell populations. Unexpectedly, in addition to some known iron‐related genes (e.g., PCBP1 best meets the criteria for anti‐immunosenescence. PCBP1 displays higher expression levels in various immune cell types of the long‐lived species in spleen and liver, both of which are important organs participating in iron storage and recycling, but not in lung. Also, PCBP1 expression decreases with age in both splenic and hepatic macrophages of human and mouse. Furthermore, the knockdown of Pcbp1 in multiple cell lines verify its effect on iron metabolism and anti‐immunosenescence. In a recent study, PCBP1 protects hepatocytes from lipid peroxidation and oxidative‐stress by controlling the labile iron pool (Protchenko et al., PCBP1 takes part in numerous immune functions. For example, PCBP1 modulates innate immune response by promoting cGAS binding to viral DNA (Liao et al., PCBP1 is also upregulated in activated T cells and prevents the conversion of effector T cells to regulatory T cells (Ansa‐Addo et al., PCBP1 in splenic immune cells may enable a healthy immune system, and thus is important for anti‐immunosenescence.Among these anti‐immunosenescence genes, the iron chaperone Pcbp1 can be regulated by two TFs, Rela and Ctcf in mouse splenic immune cells. Knocking down Rela or Ctcf significantly downregulate the expression of Pcbp1, and decreased expression levels of Rela and Ctcf are detected during aging. A previous study found that the loss of Rela would cause ferroptosis in intestinal epithelial cells (Xu et al., Ctcf deficiency leads to a decrease in cytochrome C and ISCU proteins, which leaded to ROS accumulation and lipid peroxidation (Roy et al., Rela and Ctfc can regulate Pcbp1 expression, and the knockdown of Pcbp1 in the cell lines affects the expression of ferroptosis‐related genes. Therefore, we speculate that the decreased expressions of Rela and Ctcf downregulate the expression of Pcbp1, thereby affecting iron homeostasis, which in turn aggravates splenic immunosenescence.Finally, we find In summary, based on our constructed bat reference genome, we perform a systematical comparison of splenic immune cells between three long‐lived mammals and mouse. We detect a close relationship between B:T cell ratio and immunosenescence, and validate several iron‐related genes exhibiting anti‐immunosenescence feature. Our findings highlight the importance of iron homeostasis in splenic anti‐immunosenescence, and provide novel insights in understanding anti‐immunosenescence and healthy longevity.J.D. and M.L. designed and supervised the study, W.H., C.H., J.L., W.D., Q.H., W.C., and L.Z. performed the experiments, Z.H. and H.S. conducted the bioinformatic analyses. J.D., M.L., Z.H., and W.H. wrote the manuscript. All authors reviewed the manuscript.The authors declare no competing interests.Figure S1.Click here for additional data file.Figure S2.Click here for additional data file.Figure S3.Click here for additional data file.Figure S4.Click here for additional data file.Figure S5.Click here for additional data file.Figure S6.Click here for additional data file.Table S1.Click here for additional data file.Table S2.Click here for additional data file.Table S3.Click here for additional data file.Table S4.Click here for additional data file.Table S5.Click here for additional data file.Table S6.Click here for additional data file.Table S7.Click here for additional data file.Table S8.Click here for additional data file.Table S9.Click here for additional data file.Table S10.Click here for additional data file.


A “resect‐and‐discard” strategy has been proposed for diminutive adenomas in the colorectum. However, this strategy is sometimes difficult to implement because of the lack of confidence in differentiating low‐grade adenoma (LGA) from advanced lesions such as high‐grade adenoma or carcinoma. To perform real‐time precise diagnosis of LGA with high confidence, we assessed whether endocytoscopy (EC) diagnosis, considering normal pit‐like structure (NP‐sign), an excellent indicator of LGA, could have additional diagnostic potential compared with conventional modalities.All the neoplastic lesions that were observed by non‐magnifying narrow‐band imaging (NBI), magnifying NBI (M‐NBI), magnifying pit pattern, and EC prior to pathological examination between 2005 and 2018 were retrospectively investigated. The neoplastic lesions were classified into two categories: LGA and other neoplastic lesions. We assessed the differential diagnostic ability of EC with NP‐sign between LGA and other neoplastic lesions compared with that of NBI, M‐NBI, pit pattern, and conventional EC in terms of sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC).A total of 1376 lesions from 1097 patients were eligible. The specificity (94.9%), accuracy (91.5%), and area under the receiver operating characteristic curve (0.95) of EC with NP‐sign were significantly higher than those of NBI, M‐NBI, pit pattern, and conventional EC.EC diagnosis with NP‐sign has significantly higher diagnostic performance for predicting colorectal LGA compared with the conventional modalities and enables stratification of neoplastic lesions for “resect‐and‐discard” with higher confidence. In recent years, the widespread application of cold polypectomy has made it safer to resect colorectal polyps ≤5 mm in size. Most diminutive polyps are benign adenomasMagnifying narrow‐band imaging (M‐NBI) and magnifying pit pattern (PIT) diagnosis are used for the differential diagnosis of colorectal neoplastic lesions. M‐NBI and PIT diagnosis provides additional diagnostic value for predicting neoplastic lesions compared with conventional diagnosis.Endocytoscopy (EC) can magnify endoscopic images to a maximum magnification of 520 times, thereby facilitating real‐time histopathologic endoscopic diagnosis.To date, no study has examined whether EC diagnosis with NP‐sign has the additional diagnostic ability for LGA compared with conventional modalities. In this retrospective analysis, we examined the differential diagnostic ability of EC diagnosis with NP‐sign for colorectal LGA compared with that of NBI, M‐NBI, PIT, and conventional EC diagnosis.This study was a single‐center, retrospective study that was conducted in the Digestive Disease Center at Showa University Northern Yokohama Hospital. The study included colorectal neoplastic lesions that were observed by NBI, M‐NBI, PIT, and EC prior to endoscopic or surgical resection between January–May 2005 and May 2018. We excluded serrated lesions including hyperplastic polyps and sessile serrated lesions. Non‐neoplastic lesions such as inflammatory polyps and juvenile polyps, non‐epithelial lesions such as malignant lymphoma, lesions associated with ulcerative colitis, and poor‐image lesions that could not withstand evaluation were also excluded. On the basis of histopathology, we divided the neoplastic lesions into two groups: LGA and advanced lesions, which we defined as high‐grade adenoma, villous adenoma, and invasive carcinoma.The study protocol was approved by the Ethics Committee of Showa University Northern Yokohama Hospital  and was registered as a University Hospital Medical Information Network clinical trial (UMIN000038117). This study was performed in accordance with the Declaration of Helsinki.Bowel preparation involved the administration of 2.0–3.0 L of polyethylene glycol solution in the morning before the procedure. Colonoscopy was performed using a video endoscopic system  with an integrated‐type endocytoscope  and an endocytoscope  with a maximum magnification of ×520. Non‐magnifying NBI diagnosis was performed following the NBI International Colorectal Endoscopic classification.In the EC classification, EC 2 is composed of slit‐like lumens and regularly arranged fusiform or roundish nuclei, representing adenomatous lesions. Some studies, however, reported that invasive cancers were included among EC 2 lesions,L,NBI, M‐NBI, PIT, and EC diagnosis corresponding to histopathological images of LGA are as follows; NBI diagnosis is type 2,The specimens were examined by one pathologist using the World Health Organization criteriap‐value < 0.05 was considered statistically significant. Statistical analyses were performed using SPSS version 22  and R version 3.6.3 .To evaluate the diagnostic ability of LGA of NBI, M‐NBI, PIT, conventional EC, and NP‐sign EC, McNemar's test was used to evaluate the sensitivity, specificity, and accuracy, and the chi‐square test with weighted generalized statistics was used to evaluate the PPV and NPV. The chi‐square test was used to evaluate the diagnostic ability of LGA in each modality and receiver operating characteristic curve. Data are presented as the mean ± standard deviation. A two‐sided A flow chart of the study analysis is shown in Figure The background clinicopathological features of the patients and lesions are listed in Table p < 0.001). The sensitivity of EC with NP‐sign was significantly higher than that of NBI (p = 0.0315), but not significantly different from that of M‐NBI (p = 0.7453) and PIT (p = 0.896); it was significantly lower than that of conventional EC (p < 0.001). The NPV of EC with NP‐sign was significantly higher than that of NBI (p < 0.001) and M‐NBI (p = 0.0057), but not significantly different from PIT (p = 0.669); it was significantly lower than conventional EC (p < 0.001). Table p < 0.001). There were no significant differences in sensitivity, specificity, PPV, NPV, and accuracy in comparison with M‐NBI, PIT, and EC diagnosis.Table I p = 0.753 and PIp < 0.001).Figure This is the first report to directly compare the diagnostic performance of NBI, M‐NBI, PIT, and conventional EC diagnosis approaches with EC diagnosis with NP‐sign for LGA. In all lesions, EC with NP‐sign had a significantly higher accuracy, specificity, and PPV for predicting colorectal LGA compared with NBI, M‐NBI, PIT, and conventional EC; these findings were confirmed by calculating AUC.Polyps ≤5 mm in size have an extremely low prevalence of invasive cancer and advanced histology.M‐NBI and PIT diagnoses are currently used for the differential diagnosis of neoplastic lesions from non‐neoplastic lesions in the colon. The diagnostic accuracy of M‐NBI in distinguishing neoplastic from non‐neoplastic lesions was significantly better than that of non‐magnifying NBI.N = 22). Also, high diagnostic ability with four conventional modalities may reflect the fact that only experts performed the investigation in this study.We previously showed that the NP‐sign in EC images is an indicator of colorectal LGA with high accuracy.Only several imagesCurrently, a high adenoma detection rate and superior diagnostic ability for colorectal cancer with artificial intelligence (AI) have been reported.The present study has some limitations. First, this was a single‐institutional investigation and a retrospectively designed study. Consequently, a regional or institutional bias could exist. In addition, whether endoscopists had low or high confidence was unclear. Second, EC observation was not performed for all neoplastic lesions in our facility. Furthermore, lesions diagnosed by non‐experts were not included. Consequently, a selection bias could exist. A prospective multicenter study including non‐experts should be performed, and the confidence level should be described.In conclusion, we have reconfirmed that NP‐sign is an excellent indicator of colorectal LGA, showing additional diagnostic potential compared with conventional endoscopic modalities: EC diagnosis with NP‐sign showed a significantly higher specificity, PPV, accuracy, and AUC for predicting LGA compared with NBI, M‐NBI, PIT, and conventional EC diagnosis. Using EC diagnosis with NP‐sign will allow for the diagnosis of colorectal LGA more accurately in real time and help identify neoplastic lesions that can be managed by the “resect‐and‐discard” strategy, with higher confidence than before.None.


O‐β‐rutinoside), a citrus flavonoid from lemon juice and peel, reduces hyperglycemia and improves diabetes‐related biomarkers in prediabetes patients. Eriocitrin is first metabolized by gut microbiota, producing energy for gut cells and short chain fatty acids that play a relevant role in glycemic control. The aim of this study was to assess the effect of Eriomin®, a nutraceutical composed of 70% eriocitrin, 5% hesperidin, and 4% naringin, on the microbiota of prediabetic patients. Patients were randomly divided into two groups and received unlabeled capsules of Eriomin® (200 mg/day) or placebo during 12 weeks. After treatment with the nutraceutical, it was a 6% decrease of hyperglycemia and 22% increase of GLP‐1 blood levels of (p < .05). The profile of intestinal microorganisms, obtained by 16S rRNA sequencing of the patients' feces extract, showed changes in microbiota composition, such as lower growth of Firmicutes and less abundance of the Lachnospiraceae family. The family Ruminococcaceae increased and Blautia genus reduced with Eriomin® supplementation. In additional, Blautia was positively correlated with hyperglycemia reduction. In conclusion, the nutraceutical Eriomin® moderately reduced the growth of microorganisms associated with intestinal dysbiosis and increased the abundance of beneficial bacteria. Changes promoted mainly by the flavonoid eriocitrin in the microbiota were related to a lower glycemic level and increased production of GLP‐1 in patients with prediabetes.Eriocitrin  had 6% reduction in hyperglycemia and 22% increase in GLP‐1 blood levels. Intestinal microorganisms showed lower Firmicutes growth and less  For example, elevated blood glucose, dyslipidemia, and prehypertension are frequent and measurable signs that precede the development of type 2 diabetes, atherosclerosis, and cardiovascular disease  produced by gut bacteria , a citrus flavonoid found primarily in lemon peel, is recognized for its anti‐inflammatory and antioxidant properties, and it has the potential to be used in diabetes therapy  fasting blood glucose of 5.6–6.9 mmol/L, (2) glucose intolerance, as assessed by glucose tolerance test (7.8–11 mmol/L); (3) glycated hemoglobin (HBA1C) of 5.7–6.4% . The procedures performed followed the ethical guidelines of the National Health Council (Res. 466/12) and the Declaration of Helsinki (1964), and all participants voluntarily signed an informed consent form before starting the study.The experimental protocol was approved by the Ethics Committee of the Pharmacy School, UNESP (CAEE: 67610217.6.0000.5426) and registered at 2.2n = 25) or the placebo (n = 20). They received instructions to maintain their usual diet during the intervention and minimize the intake of citrus foods and flavonoid‐rich beverages, such as coffee, tea, cocoa, fruit juice, and wine. Eriomin® and placebo capsules in unlabeled vials were provided to the participants every 2 weeks. The volunteers took one capsule per day with water after dinner for 12 weeks. Sixteen subjects were excluded during the experimental period due to moving away (n = 2), incorrect or irregular use of capsules (n = 10), use of antibiotics due to an unrelated problem (n = 1), and intentional weight loss (n = 3). Twenty‐nine subjects who followed the experimental protocol recommendations were included in the final analysis. The chosen dose of Eriomin® (200 mg/day) was based on our previous study , and kept at −80°C in a deep freezer  until analysis.2.52, 0.2 mmol/L dNTP mixture, 0.2 μmol/L of each primer, and 1 μL of DNA for each sample. In step 2, each sample was encoded with a unique back‐and‐forth barcode combination with an Illumina P5 adapter string, a unique 8 nt barcode, a partial match string of the lead adapter used in step 1, and reverse primers with an Illumina P7 adapter. The PCR reaction in step 2 contained a final concentration of 0.2 μmol/L of each primer with a unique barcode and 1 μL of the product of the PCR reaction in step 1. The final product was quantified on the Qubit instrument using the kit of Qubit Broad Range DNA (Invitrogen), and the individual amplicons were pooled in equal concentrations. The pooled library was cleaned using Ampure XP beads (Beckman Coulter), and the band of interest was subjected to isolation by 1.5% gel electrophoresis (Sage Science). The library was quantified via qPCR followed by 300 bp paired‐end sequencing using an Illumina MiSeq instrument at the Genome Center DNA Technologies Core at UC Davis.DNA extraction from stool samples was performed using the “PowerLyzer @PowerSoil DNA Isolation Kit” (Qiagen). Primers 319F/806R were used to amplify the V3–V4 region of the 16S rRNA. In step 1, the forward and reverse primers contained a sequence of Illumina tags, a variable‐length spacer, a binding sequence, and the target sequence 16S to increase diversity and improve the quality of sequencing and execution. Each 25 μL PCR reaction contained a Kapa2G Robust Hot Start Polymerase unit (Kapa Biosystems), 1.5 mmol/L MgClhttp://github.com/msettles/dbcAmplicons). Non‐immersed direct and reverse readings were imported into QIIME2 version 2017.12 (https://qiime2.org), and the sequence variants were determined following the DADA2 analysis pipeline. To classify the sequences according to their taxonomic information, the q2‐feature‐classifier plugin was used according to the VSEARCH alignment method . The homeostasis model assessment of insulin resistance (HOMA‐IR) was estimated using a cutoff point ≥2.71 , lean mass (kg), fat mass (kg), body fat (%), and visceral fat area (cm2). Participants were instructed to fast for 2 h before bioimpedance, not drink alcohol or caffeine in the last 24 h, wear light clothes, urinate 20 min before the test, remove any type of metallic adornment, and not practice physical activity in the last 24 h. Waist circumference was measured at the midpoint between the lower border of the last rib and the top of the iliac crest : weight (kg), height (m), body mass index (BMI)  during the first and last week of the study. Participants recorded in detail everything they ate or drank, including the culinary preparations , as well as the added salt, sugar, seasonings, and sauces. Once completed, a nutritionist reviewed the diary with each patient to add any missing information.Mean daily food intake was estimated on the basis of the 3 days recorded. The analysis of energy, macronutrient, and micronutrient intake was performed using the DietBox® software, according to the Brazilian Food Composition Table , was used to detect changes in biochemical, clinical, and dietetic factors.p ≤ .05.Unilateral ANOVA  and Kruskal–Wallis  were used to identify differences between microbiota parameters at the baseline and at the end experiment. Statistical analysis was performed using SigmaStat 3.0 or BioEstat 5.0 software, and statistical significance considered was Pearson correlation analysis was used to evaluate the correlation between gut microbiota and biochemical variables (fasting glucose) in the beginning and after 12 weeks of Eriomin® treatment. A correlation network plot was generated, and correlation magnitudes >1.0 (strong co‐abundance relationships) and <−1.0 (strong co‐exclusion relationships) were plotted. Visualization of the network was performed by XLSTAT software.3n = 21) and women (n = 24), aged between 32 and 69 years, selected according to the prediabetes criteria from ADA , while patients who received the placebo remained with unchanged levels over time (Table p ≤ .05), whereas the placebo intervention revealed no change , above the Total Energy Expenditure  for these obese and sedentary individuals , whereas the placebo group showed no statistical difference , before and after supplementation. Phylum Actinobacteria was the second most abundant, in average 3.5% of the total phyla, and after 12 weeks increased 1.5% with Eriomin®, but decreased 0.6% with placebo. Together, Bacteroidetes and Proteobacteria accounted for less than 3% of the total phyla abundance, and decreased slightly in both groups. This profile shows a microbiota in dysbiosis  and Blautia genus (>35%) before supplementation. Ruminococcaceae family increased 38% after 12 weeks of Eriomin®, in contrast with a decrease of 31% with placebo , and lower levels of Prevotella genus, while placebo it not changed  while placebo increased it by 11%, showing that Eriomin® attenuated the growth of this bacteria family. In contrast, the Ruminococcaceae family increased by 38% with Eriomin®, but decreased by 31% with the placebo. This family has been associated with the fermentation of complex carbohydrates, such as fibers and resistant starch, and polyphenols, to produce SCFA. Some SCFA, such as propionic acid, can strength the intestinal barrier and reduce systemic low‐grade inflammation associated with glucose intolerance and diabetes  and high consumption of fats and saturated fatty acids, combined with low intake of dietary fiber (<25 g/day) was observed for all patients. Dietary fiber intake is recognized as one of the important mechanisms for the health of the microbiota, as it provides essential nutrients for the growth of fermentable bacteria, such as Ruminococcaceae family, which are responsible for the production of short‐chain fatty acids ; formal analysis ; writing – original draft . Carolina B. Ribeiro: Data curation ; formal analysis . Thais B. Cesar: Conceptualization ; formal analysis ; funding acquisition ; project administration ; writing – original draft ; writing – review and editing . Dragan Milenkovic: Formal analysis ; writing – review and editing . Lucelia Cabral: Formal analysis . Melline F. Noronha: Formal analysis . Katia Sivieri: Conceptualization ; methodology ; supervision ; writing – review and editing .This study was funded by a grant from Ingredients by Nature  and supported by a Coordination for the Improvement of Education Personnel (CAPES) scholarship to FR and CR.The authors declare no conflicts of interest. The sponsors had no role in the design, execution, interpretation, or writing of the study.ClinicalTrials.gov (NCT03215043). The procedures performed followed the ethical guidelines of the National Health Council (Res. 466/12) and the Declaration of Helsinki (1964), and all participants voluntarily signed an informed consent form before starting the study.The experimental protocol was approved by the Ethics Committee of the Pharmacy School, UNESP (CAEE: 67610217.6.0000.5426) and registered at


To comprehensively investigate the implications of lymph node dissection (LND) and the prognostic impact of the number of lymph node (LN) metastases on survival in intrahepatic cholangiocarcinoma (ICC) using a large‐scale study.Patients who underwent surgical resection for ICC between 2004 and 2018 were identified from the Surveillance, Epidemiology, and End Results (SEER) registries. The Kaplan–Meier and log‐rank tests were used to compare cancer‐specific survival (CSS) and overall survival (OS) between different groups. Propensity score matching (PSM) and subgroup analyses were performed to balance potential confounding factors. A multivariate Cox proportional hazards regression model was used to identify prognostic factors of survival outcomes. Restricted cubic splines fitted in the Cox proportional hazard regression models were also conducted to examine associations between continuous variables and outcomes.p < 0.001). Patients who received LND were further categorized as having no nodal metastasis (N0), 1–2 LNM (N1), or ≥3 LNM (N2) according to the number of LNM. The Kaplan–Meier curves showed that the mortality risk of patients with N0, N1, and N2 disease  increased significantly, except for patients who had <6 LNs harvested. On multivariable survival analysis, a higher nodal stage  was an independent prognostic risk factor for survival.In all, 1028 patients were enrolled. There were 652 (63.4%) patients undergoing LND, with lymph node metastasis (LNM) confirmed in 212 (32.5%) cases. Patients receiving LND did not show better survival outcomes than those receiving non‐LND (NLND). We divided the LND group into two subgroups: patients with LNM (+) and those without LNM (−). Among these three groups, patients with LNM experienced the worst CSS and OS, while NLND patients had similar survival times to LNM (−) patients. Restricted cubic spline analysis indicated that an increased number of LNM was associated with a decreased chance of survival  staging system simply classified the N stage as N0 and N1 on the basis of LN status. The implications of lymph node dissection (LND) and the prognostic impact of the number of lymph node metastases on survival in intrahepatic cholangiocarcinoma (ICC) remain unclear. By analyzing a large cohort of more than 1000 resected ICC patients, the present study showed that despite the lack of a clear survival benefit of LND in patients with ICC, a Significant positive association between the number of LNM and poor outcomes was observed. We still suggest adequate LND by examining at least 6 lymph nodes to ensure precise staging. On this basis, the recently proposed nodal classification of N0, N1, and N2 stages may also allow better prognostic stratification of ICC patients. The inclusion criteria included the following: (1) the primary site code for liver (C22.0) and intrahepatic bile duct (C22.1) with histology code 8160/3 (cholangiocarcinoma) based on the third edition International Classification of Disease for Oncology (ICD‐O‐3); (2) patients aged 18–80 years old with the first and only one primary malignancy; (3) patients confirmed by histology who received cancer‐directed surgery (surgery of primary site codes: 20–90); (4) patients with known information on LND status, radiation, tumor size, tumor (T) stage, and without distant metastasis; and (5) patients who survived more than 1 month after surgery. Patients with unknown survival data and those who underwent LND but without information on LN status were excluded. The following variables were collected from the database: age, year of diagnosis, sex, race, marital status, tumor size, distant metastasis, tumor grade, the extent of surgery, chemotherapy status, radiation therapy status, follow‐up outcome, survival months, the scope of LND, LN status, number of examined lymph nodes (NELN), and metastatic LNs. The T‐stage of patients was reclassified according to the eighth edition of the AJCC staging system for ICC. Cancer‐specific survival (CSS) was calculated from the date of diagnosis to the date of death attributed to ICC. Overall survival (OS) was defined as the period from the date of diagnosis to the date of death.2.2p value <0.05 in a two‐tailed test was considered statistically significant. All analyses were conducted using R software version 4.0.2 .Categorical variables were compared by the Fisher's exact tests across groups. Propensity‐score matching (PSM) was performed by using the 1:1 nearest neighbor matching method with a caliper of 0.05 on the propensity scale to balance confounding factors between the LND group and the non‐LND group (NLND). The matching variables included sex, age, year of diagnosis, race, marital status, tumor grade, T‐stage, tumor size, and treatment options . The CSS and OS of ICC patients were estimated with the Kaplan–Meier method and then compared using log‐rank tests. Univariate and multivariate Cox proportional hazard regression analyses were used to evaluate the effect of each factor on prognosis. The outcome risks of CSS and OS were expressed as hazard ratios (HR) with corresponding 95% confidence intervals (CI). Subgroup analyses were also performed to clarify the effect of LND on the outcome. Among patients who underwent LND, we used restricted cubic splines (RCS) with four knots based on Cox proportional hazards regression models to flexibly model the association of the number of LNM with CSS and OS. A 33.1There were 1028 patients with ICC who underwent curative resection in the SEER database from 2004 to 2018 and met the inclusion and exclusion criteria Figure . Of thos3.2p = 0.002) and OS  than patients without LND  had the worst CSS, followed by LNM (−) patients and NLND patients  51 vs. NLND 50 months, p = 0.920) , while NLND patients showed similar survival time to LNM (−) patients  46 vs. NLND 43 months, p = 0.450) . Nevertheless, the LNM (+) group suffered significantly worse survival than the other two groups . Consistent with univariate analysis, multivariable analysis confirmed that as compared with the NLND group, the survival outcomes of the LNM (−) subgroup were comparable (p > 0.05), whereas the LNM (+) subgroup was associated with significantly poorer CSS  and OS   and 34.8% , respectively. The median follow‐up period was 35 months (interquartile range [IQR]: 16–94 months). Interestingly, in the Kaplan–Meier analysis, patients with LND had poorer CSS  Figure . Likewis) Figure . In subg) Figure  among th) Figure .3.3p < 0.001) and the nonlinear association (p = 0.024). The trend between the number of metastatic LNs and CSS was consistent when stratified by NELN, sex, the extent of surgery, chemotherapy, and radiation therapy status  and OS . Moreover, after adjusting for confounding factors, N1  and N2  were independent prognostic factors of both CSS and OS . However, among patients who had NELN <6  or OS  between the N1 and N2 groups. We also found that NELN ≥6  was an independent risk factor for LNM (Table p > 0.05)  Figure . Hence, 4By analyzing a large cohort of more than 1000 resected ICC patients, the present study showed that LND does not seem to improve the outcomes of patients. Among patients who underwent LND, a higher number of LNM was correlated with worse outcomes; thus, LND is essential for optimal staging and prognostic assessment. Moreover, retrieval of at least six LNs is recommended. Relying on the adequacy of LND, the recent arising nodal classification of N0, N1, and N2 has good discrimination to stratify outcomes.Currently, the value of LND remains a matter of debate in the surgical treatment of ICC. Some studies have indicated that LND does not improve patient survival. Others suggested that it was associated with better long‐term outcomes and should be performed routinely. Tomoaki Yoh et al. analyzed data from three tertiary hepatobiliary centers and found that lymphadenectomy was associated with a better prognosis for patients with node‐negative ICC.In general, the presence of regional LNM often portends a poor prognosis.To the best of our knowledge, this is a population‐based real‐world study using large sample sizes with rigorous statistical analysis on such issues. Nonetheless, there were some limitations to our study. Although PSM in addition to conventional multivariate analysis were conducted, the nature of the retrospective database led to intrinsic selection bias. Patients with higher probability of being node‐positive, or more advanced‐stage disease are prone to receive LND. In addition, the SEER database itself does not provide information about the detailed extent of lymphadenectomy, preoperative imaging data, physical condition, and molecular alterations of tumors, which could influence the treatment selection and the survival outcome.5This population‐based study reveals that the LND failed to show survival benefit in patients with ICC. A significant positive association between the number of LNM and poor outcomes was observed. LND with at least 6 LNs harvested plays an important role for accurate nodal staging. With adequate LND, the recently proposed nodal classification of N0, N1, and N2 is of considerable clinical significance in the prognostic stratification of ICC patients.Jiang Zhu: Conceptualization ; data curation ; formal analysis ; funding acquisition ; investigation ; project administration ; resources ; software ; supervision ; validation ; visualization ; writing – original draft ; writing – review and editing . Chang Liu: Formal analysis ; software ; writing – review and editing . Hui Li: Data curation . Haoyu Ren: Data curation . Yunshi Cai: Investigation . Tian Lan: Methodology . Hong Wu: Conceptualization ; project administration ; resources ; software ; visualization ; writing – original draft ; writing – review and editing .This work was supported by the National Natural Science Foundation of China , the China Postdoctoral Science Foundation (2022TQ0393).The authors declare that they have no competing interests.Ethical approval and written informed consent were not needed, as the study is based on anonymized publicly available data.Figure S1.Click here for additional data file.Figure S2.Click here for additional data file.Figure S3.Click here for additional data file.Figure S4.Click here for additional data file.Table S1.Click here for additional data file.


CR lowered VS , but not BP (p > 0.05). Blood glucose  and lipids  and TC/HDL ) were unchanged. RQ decreased with CR , though REE was unchanged (p = 0.83). The 3‐day CR diet significantly improved fat metabolism, body weight and composition, and vascular stiffness.Overweight and obesity (Ow/Ob) is a risk factor for cardiometabolic disease. Caloric restriction (CR) have been investigated but little is known about the acute effects of CR and often such diets are not standardized. Thus, we aimed to assess the impact of a new standardized 3‐day CR diet  on cardiometabolic health in weight‐stable Ow/Ob individuals. In a single‐arm design, 15 Ow/Ob men and women were assessed pre‐post a 3‐day standardized CR diet; specifically, body weight/composition , blood pressure (BP), and vascular stiffness (VS), resting energy expenditure (REE), substrate utilization , and blood glucose/lipid profile). CR lowered body weight (93.1 ± 15.2 to 90.67 ± 14.4 kg,  We hypothesized that the 3‐day CR diet would induce favorable changes in body weight, body composition, metabolic function, via increased fat use, blood pressure, and blood glucose/lipid profile. This study could provide evidence on the acute efficacy of a novel 3‐day CR on body weight/composition, but also identify the potential underlying physiological mechanisms through which such dietary intervention may elicit cardiometabolic improvement. Collectively, this may provide a preliminary data for study of this diet with IF.22.12), and weight stable (±2 kg) for ≥6 months prior, and 25–65 years of age. Participants were otherwise relatively healthy without uncontrolled chronic disease  and two or fewer positive risk factors for cardiovascular disease  as described by the American College of Sports Medicine/American Heart Association Criteria .Participants were recruited via email and publicly posted flyers from the Saratoga Springs, NY community. To be included participants must have been Ow or Ob  using indirect calorimetry and ventilated hood technique   of fresh blood was used for blood lipid and glucose measurement using the cholestech ldx analyzer , which has been validated against standard clinical testing , and this marked the start of Day 1 (Monday or Tuesday). Details of the diet are provided in Tables 2.3r2 > 0.9, and coefficient of variation (cv) of <8%, and any values outside of the standard curve were not included in the final analysis.To estimate in vivo biological effects of the 3‐day CR, plasma samples were analyzed using commercially available assay kits for ketone bodies , factors that regulate metabolism , and factors that influence hunger/satiety . From glucose, mentioned above, and insulin the homeostatic model of assessment of insulin resistance (HOMA‐IR) was calculated using published formula , to yield an acceptable power of 0.8, an estimated 12 subjects would be needed . We assumed that by recruiting 20, this could allow for possible dropout/non‐compliance ensuring beyond the minimally effective sample size. Data were analyzed using open source software . The data were analyzed using paired samples t‐tests and a complementary estimate of effect size, Cohen's d, where 0.2, 0.5, and ≥0.8 represent small, medium, and large effect sizes, respectively. Perceptual data over time were analyzed using a one‐way repeated measures analysis of variance. Assumptions for these tests were run and if a violation to normality occurred, a nonparametric alternative was employed, or an adjustment to the degrees of freedom was made. Alpha was set to 0.05. Data are presented as means ± standard deviation, unless otherwise noted.In a paired samples 33.1The fifteen individuals who completed the study were nearly middle aged, with a relatively even split of men and women Table . Accordi3.2p < 0.001, d = 1.9), body mass index by 3% , body fat , and visceral fat score by 14%   and hip  circumferences were lower as well, by ca. 1% each, thus waist‐hip ratio was unaffected  or body water  in response to the 3‐day CR diet , diastolic , or mean  blood pressures , diastolic , or mean  blood pressures . The pulse wave analysis revealed that while the 3‐day CR diet had no effect on pulse pressure , it did significantly alter augmentation pressure  and augmentation index  , total cholesterol , HDL cholesterol , or TC/HDL   and LDL cholesterol tended to increase  , which is derived from the VO2. Though a significant reduction in the respiratory quotient (RQ) was observed  suggesting metabolic shift from using carbohydrates to fats  and corresponding 38% increase in the amount of fat oxidation   Figure .3.6p > 0.05, d < 0.4, Table p = 0.04, d = 1.0) and leptin  were significantly increased in response to the 3‐day CR diet in Ow/Ob men and women . Satiety did vary over time and seemed to reach a high point at the end of Day 2, which then decreased at Day 3, and to post‐diet testing on Day 4 (data not shown). The 3‐day CR diet had no significant effect on self‐reported sleep latency, or the total sleep duration over the course of the study .The 3‐day CR diet had no significant effect on self‐reported perceptions or feelings of hunger, desire to eat, or fullness  and provide evidence on an “off the shelf” way of carrying out a version of IF, as many individuals may struggle to plan and effectively carry out such dietary interventions. Such an IF approach might avoid complications associated with chronic/continuous CR   induces significant weight and fat loss, increases circulating leptin, increases fat oxidation, without much change to blood lipid profile, blood pressure, feelings of hunger, or sleep in adult men and women who are Ow or Ob. These novel findings suggest that such a diet could be beneficial as an approach to initiating weight loss in those that are Ow or Ob, or could be utilized in an intermittent fasting diet  approach to weight loss, but further studies are warranted to determine efficacy and whether such weight loss is sustained.Conceptualization, JD and SI; methodology, JD and SI.; formal analysis, AC, BY, JD, SI.; investigation, JD, AC, BY, CK, AC, SI.; resources, SI AC; data curation, AC, BY, JD, SI.; writing—original draft preparation, JD, SI, CK; writing—review and editing, JD, SI, AC, BY CK AC.; visualization, AC BY SI; supervision, SI JD; project administration, SI.; funding acquisition, SI. All authors have read and agreed to the published version of the manuscript.This research was funded by Plexus Worldwide, grant number 2204‐1028.Plexus Worldwide provided funding and product for the current study although the funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.All participants provided written informed consent prior to participation. This study was reviewed and approved by the Institutional Review Board at Skidmore College (#2204‐1028) and registered with clinicaltrials.gov (NCT05422391). This study was carried out in accordance with the principles set forth in the most recent revisions to the Declaration of Helsinki.Table S1.Click here for additional data file.Table S2.Click here for additional data file.