Atrial fibrillation (AF) is a frequent arrhythmia associated with cardiovascular morbidity and mortality. Neutrophil extracellular traps (NETs) are DNA fragments with cytoplasm proteins released from neutrophils, which are involved in various cardiovascular diseases. To elucidate the role of NETs in AF, we investigated the effect of NETs on AF progression and the secretion of NETs in AF. Results showed that: NETs induced the autophagic apoptosis of cardiomyocytes, and NETs also led to mitochondrial injury by promoting mitochondrial depolarization and ROS production. Ongoing tachy-pacing led to the structural loss of cardiomyocytes and provided potent stimuli to induce NETs secretion from neutrophils. In the meanwhile, increased Ang II in AF facilitated NETs formation through the upregulation of AKT phosphorylation, while it could not directly initiate NETosis as the autophagy was not induced. In vivo, DNase I was administrated to abrogate NETs formation, and AF-related fibrosis was ameliorated as expected. Correspondingly, the duration of the induced AF was reduced. Our study addresses the formation mechanism of NETs in AF and demonstrates the lethal effects of NETs on cardiomyocytes through the induction of mitochondrial injury and autophagic cell death, which comprehensively describes the positive feedback comprised of NETs and stimuli secreted by cardiomyocytes that sustains the progression of AF and AF related fibrosis. In China, the prevalence of AF is 1.8 percent, which increases significantly in the elderly population.5 Clinical studies have shown the 5-year recurrence rate for catheter ablation and conventional radiofrequency are 71 and 40 percent, respectively.8 Even though inflammation and fibrosis essentially orchestrate the pathogenesis and persistence of AF, the mechanism is presently far from being elucidated.9 Therefore, the further clarification of specific mechanisms of AF and the development of effective methods to control it are critical.Based on the latest publications, the main treatments for AF include medication, catheter ablation and surgical ablation.10 However, neutrophils have recently been demonstrated to secret neutrophil extracellular traps (NETs) to participate in the occurrence and development of multiple diseases. By now, chronic obstructive pulmonary disease, atherosclerosis, hepatitis, and many other sterile chronic diseases are associated with the formation of NETs, but whether NETs play a role in AF is still unclear.15The occurrence and progression of AF are closely related to the inflammatory reaction and immune cell activation. The main cell type involved in the innate immune response is neutrophils, whose main role was believed to eliminate pathogenic bacteria and injured cells in the acute inflammatory response.16 Previously we described that NETs sustain pathogenic fibrosis after acute myocardium infarction (AMI) and contribute to the formation of ventricular aneurysm through the activation of Smad and mitogen-activated protein kinase (MAPK) signaling pathways.17 As fibrosis is closely related to AF, the involvement of NETs in AF was investigated in this study. Since cardiac remodeling involves both the loss of tissue cells in situ and the proliferation of fibroblasts, we examined the lethal effects of NETs on cardiomyocytes. In addition, we also investigated whether NETosis could be initiated by stimuli secreted by cardiomyocytes in experimental in vitro model of AF.NETs are a network structure with DNA fragments as the skeleton. The DNA skeleton of NETs contains nuclear and mitochondrial DNA, with abundant neutrophil granules and cytoplasm proteins scaffolded.18 As expected, the NETs level in peripheral blood in patients with AF was significantly higher than that of patients with SR . A complex enzyme-linked immunosorbent assay (ELISA) with antimyeloperoxidase (MPO) capture antibody and anti-dsDNA detective antibody was used to determine the relative concentration of NETs as previously described. SR Fig. . The NET SR Fig. . The cor SR Fig. . Thus we SR Fig. . However SR Fig. .Fig. 1NEPreviously, we reported that NETs alone activate Smad and MAPK signaling pathways, which further induce the differentiation from fibroblast to myofibroblast. Considering that the loss of cardiomyocytes essential to cardiac remodeling and NETs contain abundant cytotoxic proteases, we further investigated whether NETs are toxic to cardiomyocytes. With Nanolive 3D-holomotomographic microscopy, we continuously monitored cardiomyocytes incubated with NETs, and atrophy along with perinuclear granule increase was observed in cardiomyocytes  production can be death-promoting, the effects of NETs on cardiomyocyte mitochondria were analyzed.ETs Fig. . To furtETs Fig. . MitochoETs Fig. . In addiETs Fig. . As CCK-ETs Fig. .21 Previous studies demonstrated that elevated Ang II in AF induces cardiac remodeling, and phosphorylation of Akt is upregulated by Ang II type 1 (AT1) /receptor signaling pathway activation.22 Similarly to previous reports, we found that Ang II increased in the peripheral blood of patients with AF  when neutrophils incubated with Ang II  and subsequently ameliorate autophagy. it Fig. .Fig. 4AnPhorbol myristate acetate (PMA), a common phorbol ester, strongly induces the activation of neutrophils. Since Ang II could not directly initiate NETosis, we then investigated the effect of Ang II on PMA-induced NETosis. Unlike Ang II immediately induce apoptosis of neutrophils, increased cleaved caspase 3 was not observed in rat neutrophils incubated with both PMA and Ang II (with a concentration less than 10 μM) Fig. . The phoIsolated neutrophils from the peripheral blood of donors were then incubated with PMA or PMA+ Ang II. As 10 μM Ang II did not induce significant apoptosis, this concentration was mostly employed in the subsequent experiments. Co-incubation with PMA and Ang II significantly increased SYTOX Green positive rate, which was more significant than that produced by Ang II or PMA alone Fig. . NETs se26 Therefore, we hypothesized that tachy-paced cardiomyocytes may release mtDNA to induce NETosis. To prove this hypothesis, we conducted tachy-pacing  as experimental AF or normal pacing as negative control  on neonatal rat cardiomyocytes as described previously, and the supernatants were collected , and Wiersma et al. demonstrated that cardiomyocytes undergo mitochondrial dysfunction after tachy-pacing.ion Fig. . We firsion Fig. . In addiion Fig. .28Fig. 529 Thus, Celigo whole view analysis was used to analyze NETs secretion through SYTOX Green staining of extracellular DNA. As expected, the SYTOX Green count increased after incubation with supernatants of tachy-paced cardiomyocytes and more significantly with additional administration of Ang II, which was similar compared to that of PMA  was recorded to ensure a successful induction. The injection was administrated every other day for two fortnights, along with additional injection of DNase I solution or the same volume of normal saline. The formation of rat NETs was compared with citrullinated Histone 3 (cit-H3) in the left atrium (LA) determined through western blot Fig. . Masson 17 Furthermore, Mangold et al. have demonstrated that NETs are important determinants of microvascular occlusion (MVO) formation in STEMI patients.30 Colchicine has been found to be efficient in improving cardiac function through the reduction of cardiac remodeling after MI as its inhibiting effect on NETosis.31 In addition, we also found that NETs activate myofibroblast differentiation and participate in the formation of ventricular aneurysm after MI.32 However, Wei et al. indicate that the absence of EDIL3 leads to increased NETs formation, which mediates the differentiation of macrophages and benefits the longstanding fibrosis after MI.33 This is probably related to the action of S100A9: long-term S100A9 blockade negatively impacts cardiac recovery34 and counterbalances the beneficial effects of short-term therapy.35 And in this study, we described the elevated NETs concentration in both the peripheral blood and LAA of patients with atrial fibrillation when compared to patients with SR. Possibly due to the combined pathological conditions, there was no significant difference of infiltrated neutrophils identified between patients with or without AF  through multiple mechanisms. Of all these potential mechanisms, innate immune response and cardiac fibrosis after MI have been investigated most extensively. A comparison of the ST-elevation myocardial infarction (STEMI) patients with low-level and high-level NETs uncovered that NETs would be positively correlated with excessive systemic inflammation in STEMI patients, while negatively associated with the matured atheroma.2+ overload and excessive mitochondrial ROS production.36 In this study, we demonstrated that NETs could induce the mitochondrial injury of cardiomyocytes. As mitochondrial injury and cardiac apoptosis are not evident in AF rats, we instead performed the experimental model of AF in vitro , which is well established.27 In the meanwhile, structural damage was observed in tachy-paced cardiomyocytes, and the supernatants with increased mtDNA induced the secretion of NETs. Once AF occurred, cardiomyocytes with mitochondrial dysfunction would secret mtDNA along with other stimuli to activate NETosis, and NETs in turn will further deteriorate the mitochondrial injury, which as a whole forms the positive feedback loop to sustain NETs formation and mitochondrial injury. As NETs could promote the myofibroblast differentiation and fibrosis, AF-related fibrosis will also be sustained thereafter. However, the damage caused by AF on the myocardium seems to be less severe in vivo and other protective mechanisms may exist to reduce the mitochondrial injury and cardiac apoptosis.Besides fibroblast activation, the loss of cardiomyocytes is also essential to cardiac remodeling. Mitochondrial dysfunction has been found to contribute to AF initiation and progression, which is caused by mitochondrial Ca37 In our study, autophagy contributed to the NETs-induced death of cardiomyocytes. In rats, induction of AF also resulted in autophagy, whereas Dnase I administration compromised the upregulation of autophagy and decreased the duration of induced AF. We also analyzed the possible toll-like receptors (TLRs) activated by NETs, of which TLR4 was significantly upregulated , which is induced by NETs (data not shown). In fibroblast, sting signaling pathway is activated by internalized NETs and further increases the phosphorylation of TANK-binding kinase 1 (TBK-1) and interferon regulatory factor 3 (IRF-3), which is protective as it blocks the phosphorylation of smad3.46 Sting-mediated autophagy degrades phosphorylated TBK-1 (p-TBK-1) and abrogates the protective effect of the sting signaling pathway.47 When NETs are abundantly accumulating, the inhibition of autophagy may be protective, which restrains fibroblast differentiation and reduces myocardial injury. Therefore, pharmacological intervention against autophagy may be protective against fibrosis in the initiation and persistence stage of AF.In this research, we also demonstrated the upregulation of autophagy in cardiomyocytes after NETs incubation. Yuan et al. demonstrated autophagy-related gene7 (ATG7) is significantly upregulated in AF patients, and ATG7 knockdown restores the shortened atrial effective refractory period and alleviates the AF vulnerability.48The pro-fibrosis effect of NETs in cardiovascular disease may not be limited to its direct effects on cardiomyocytes or fibroblasts. On NETs, many active scaffolded proteases may transform the proinflammatory cytokines from the precursor to the activated form. We identified the profibrogenic role of IL-36γ after MI, which activated the MAPK signaling pathway through IL-36R activation. The initial level of the IL-36γ in normal mice reached 2 μg per 0.1 g myocardium; however, despite the significant upregulation of the IL-36R signaling pathway, IL-36γ in myocardium did not increased significantly after MI (data not shown). The possible regulation mechanism of IL-36γ after MI may be that NETs with cathepsin G and elastase are secreted and transform pro-IL-36γ into the activated form. Besides cytokine activation, NETs promote thrombo-inflammation and lead to vascular occlusions.51 The formation of micro-thrombus further facilitates NETs formation and result in the ischemia of the myocardium and the mitochondrial dysfunction of cardiomyocytes.48 In addition, we identified NETs in the mural thrombi obtained from LA of patients with AF  and P-selectin deprived from the endothelium, which promotes thrombosis by providing scaffold and recruiting of XIIa factor, platelets, and red blood cells.Specific-pathogen-free (SPF) Sprague-Dawley (SD) rats, weighing 250 g, were purchased from Dashuo Biomedical Technique Company . Rats were housed under SPF conditions and grown in an environment of appropriate temperature and humidity, with sufficient water and food. The animal experiments were performed in compliance with the guidelines of the Ethics Committee of West China Hospital of Sichuan University under a project license (No. 20211404 A),The study was approved by the Ethics Committee of West China Hospital of Sichuan University and followed the principles of the Helsinki Declaration. All samples were obtained after informed consent. Peripheral blood was obtained before surgery, while coronary blood was obtained at the coronary sinus orifice in the short time window before cardiopulmonary bypass. Sera obtained from blood samples through centrifugation were stored at −80 °C. LA tissue was divided into 0.1 g portions and homogenized with 1 mL PBS, centrifuged at 3000 rpm for 30 min, and stored at −80 °C.18Quantification of NETs in sera and homogenates was performed using a complex ELISA combining anti-MPO  as capture antibody and biotin-conjugated anti-dsDNA  as detective antibody.LA was embedded in paraffin and used for immunohistochemistry or immunofluorescence (IF) analyses. Masson’s trichrome was used to compare the collagen volume. For IF staining of heart sections, primary antibodies anti-MPO , neutrophil elastase  and cit-H3  antibodies were used to identify NETs in LA. Cells were fixed with 4% paraformaldehyde for 15 min and NETs were fixed for 30 min to 1 h. Followed by permeabilization with 0.5% Triton-X-100  for 10 min, and sealing with the corresponding serum . Besides using primary antibodies to identify NETs, anti-LC3B  and anti-p62  antibodies were incorporated for the analysis of autophagy. The primary antibodies were incubated overnight at 4 °C, while the secondary antibodies were incubated at room temperature for 1 h in a dark room. DAPI (10 μg/mL) was used to stain nuclei.3, repeatedly digested in 5 mL PBS containing 1% trypsin  and collagenase type II  at 37 °C for 10 min, and stopped by transferring the supernatants to an equal volume of Dulbecco’s modified Eagle’s medium  with 10% fetal bovine serum . The cell suspension was centrifuged at 1000 rpm for 10 min and cells were resuspended in DMEM/low glucose supplemented with Glutamax , 10% FBS and 1% penicillin-streptomycin , from which the fibroblasts were further removed through differential adherence for 30 min. The supernatants were then transferred to a six-well plate and cultured at 37 °C and 5% CO2 for 24 hours, after which the medium was replaced with DMEM/high glucose supplemented with 10% FBS and 1% PS.Cardiomyocytes were isolated from the hearts of neonatal SD rats. Hearts were cut into patches of 1 mmBefore any treatment, neonatal cardiomyocytes were cultured in the replaced medium for 24 h. NETs concentration was determined by Picogreen dsDNA assay kits  and adjusted to 5–10 μg/mL. Neonatal cardiomyocytes were incubated in the medium containing NETs for further analysis, whereas the same volume of normal culture medium was used as blank and DNase I degraded NETs as the negative control. Treatments were conducted for 24 hours.The femur and tibia of rats (2-3) were detached from the other connected tissues and washed three times in Hank’s balanced salt solution (HBSS). A Syringe was then used to rinse the bone marrow with Roswell Park Memorial Institute (RPMI) medium. Lysis of red blood cells (RBCs) eliminated the RBC contamination. Percoll gradients of 55%, 65%, 70%, and 80% were used to isolate neutrophils. The 70% Percoll fraction, including the cell layers at the boundaries, was collected and washed with HBSS for further use.8–1 × 108 isolated neutrophils were resuspended in 4 mL RMPI (supplemented with 10% FBS and 1% PS) in 10 cm plates and incubated with 500 nM PMA  for 3 hours to activate NETosis. For the negative control, DNase I  was used to degrade NETs. To collect NETs, the medium was removed, and NETs attached to the plate were washed gently with HBSS once, followed by intense flushing with fresh medium to detach the NETs from the plate. The washing medium was then collected and pipetted frequently for complete resuspension. Floating cells were removed by centrifuge at 300 g for 10 min. Finally, the suspension containing NETs was stored at −20 °C and used within 2 weeks.A total of 0.5 × 10To isolate human neutrophils, the isolation strategy was based on Polymorphrep . Peripheral blood (5 ml) was added onto the same volume of Polymorphrep in 15 mL centrifuge tubes and centrifuged at 800 g × 30 min at room temperature. Neutrophils between the Polymorphrep solution and water were collected and the remaining RBCs were lysed. Neutrophils were resuspended in RPMI + 10% FBS + 1% PS for immediate use. As the positive control, neutrophils were routinely incubated with 100 nM PMA. However, when analyzing the synergistically stimulating effects of Ang II on NETosis, only 10 nM PMA was used. For Ang II incubation, concentrations varied from 0.1 to 100 μM.For live cell 3D holotomography, cardiomyocytes were settled onto a 35 mm plate with glass bottom (diameter = 15 mm). The culture medium was discarded, cells were washed three times with HBSS, and the medium containing NETs was then added. The acquisition was set for refractive index  for a time-lapse of 15 h every 15 min in a Nanolive Fluo-3D Cell Explorer®  microscope. At the end of the experiment, images were exported using Steve software v.2.6® (Nanolive). For zoomed video, the region of interest was cropped and the same procedure described above was applied.53 In brief, a transmission and epifluorescence optical setup for one bright-field (BF) and four fluorescence (FL) imaging channels  were included and optimized for analysis. The fluorescence filter was set for the corresponding colors as follows: blue , green , red , and far red . Auto and manual focus were provided, with the focus found in BF. After the focus was registered, highly uniform images of the entire plates  were captured rapidly at different channels. For analysis of NETs formation, Hoechst  and SYTOX Green  were added to reach final concentrations of 10 ng/mL and 300 nM, and incubated for 30 and 10 min, respectively.54 For the analysis of cell death, besides Hoechst Propidium Iodide  was diluted 1:100 and added just before analysis according to manufacturer’s instruction. For analysis of mitochondrial ROS, cells were incubated with Hoechst and 10 μM MitoSOX  for 30 min. The fluorescent dyes were mixed by gentle pipetting.The Celigo Image Cytometer instrument has been used in high-throughput cell-based assays.Samples were fixed with three percent glutaraldehyde for 24 hours, followed by postfixed with one percent osmium tetroxide. Samples were subsequently dehydrated in series acetone and infiltrated in Epon 812 for 30 to 60 minutes each time, which were finally embedded. The semithin sections were stained with methylene blue and ultrathin sections were cut with a diamond knife, and stained with uranyl acetate and lead citrate. Sections were examined with JEM-1400-FLASH Transmission Electron Microscope.The membrane potential of mitochondria was determined with the JC-1 probe  as previously described. Briefly, cells were incubated with 500 nM JC-1 according to the manufacturer’s recommendation. Images were observed through fluorescence microscopy and photos were obtained . The intensity ratio of green fluorescence vs red fluorescence was calculated using the Image J software . And the fluorescence intensity was also detected by the fluorescence microplate reader .Tissue homogenates and cell lysates were subjected to western blot to screen for fibrosis and NETs formation. Target proteins were separated from the lysates, transferred to a PVDF film and determined through chemiluminescence. The antibodies used included the following: anti-GAPDH , anti-Collagen I , anti-p-p38 , anti-p38 , anti-p-Smad2 , anti-Smad2 , anti-p-Smad3 , anti-Smad3 , anti-Caspase 3 , anti-Cleaved-caspase 3 , anti-Beclin-1 , anti-p62 , anti-LC3B , anti-Cit-H3 , and anti-H3  antibodies.Rat neonatal cardiomyocytes assigned to the normal control group were subjected to 1 Hz , 40 V and 10-ms pulses. For cardiomyocytes of the tachypacing group, the pacing rate was increased to 6 Hz, and the other parameters were unchanged. The C-pace EP culture stimulator was used to fire programmed pacing signals and the duration was usually less than 6 hours.g for 5 min at 4 °C, and the supernatants were carefully collected by avoiding touching the pellets with pipette tips. Lastly, the supernatants were further centrifuged at 18,000 g at 4 °C for 15 min, The resulting supernatants were further processed for DNA isolation using the DNeasy blood and tissue kits  according to the manufacturer’s instruction. To determine the mtDNA in cell-free DNA, quantitative real-time polymerase chain reaction (qPCR) was then performed. Primer : forward TGGCCTTCCTCACCCTAGTA; reverse TTAGGGGGCGTATGGGTTCT. The plasma mtDNA concentration was:The supernatants (100 mL) were mixed with PBS (100 mL), followed by brief vortexing. The mixture was centrifuged at 700 dna is the total volume of plasma DNA obtained after extraction, Vpcr is the volume of plasma DNA solution used for PCR, and Vext is the volume of plasma extracted. To compare the relative concentrations, we first calculated the average concentration of the normal control and then calculated the relative concentration ratios for comparison.Q is the number of determined mitochondrial DNA copies, V57 Briefly, the AF group was induced with Ach (66 μg/mL)-CaCl2 (50 mg/mL) with 0.1 mL/100 g dose via the tail vein injection for 28 days. In the first Four days, rats were selected for the successful establishment of the AF model and rats without AF were excluded. The remaining rats were randomly assigned to group AF or AF + DNase I. The AF + DNase I group was administrated DNase I by intravenous injection once a day for the following 24 days at a therapeutic dose (0.1 mg/kg); an hour later, Ach-CaCl2 was re-administered.58 Electrocardiogram showed that the P wave disappeared and the f wave appeared as in the typical AF ECG. The P wave appeared and the f wave disappeared as a sign of AF to restore sinus rhythm. For sample collection, rats were anesthetized, peripheral blood was drained from the right ventricle and left atrium tissues were collected.SD rats were randomly assigned to the blank, AF or AF + DNase I groups. The pharmacological induction of AF in rats was described previously.P < 0.05 was considered statistically significant. Data are presented as mean ± SD.Results are presented as the mean ± standard deviation. Groups were compared through analysis of variance and the Student’s t-test. All statistical analyses were performed using Prism 7 software . Supplementary informationsupplementary movie 1supplementary movie 2


There is limited longitudinal evidence supporting the association between the hypertriglyceridemic-waist (HTGW) phenotype and hyperuricemia. This study aimed to examine the longitudinal relationship between hyperuricemia and the HTGW phenotype among males and females.A total of 5562 hyperuricemia-free participants aged 45 or over from the China Health and Retirement Longitudinal Study (mean age: 59.0) were followed for 4 years. The HTGW phenotype was defined as having elevated triglyceride levels and enlarged waist circumference . Hyperuricemia was determined by uric acid cutoffs .During the four-year follow-up, 549 (9.9%) incident hyperuricemia cases were ascertained. Compared with those with normal levels of triglycerides and waist circumference, participants with the HTGW phenotype had the highest risk of hyperuricemia , followed by an OR of 1.96 (95% CI: 1.40 to 2.74) for only higher triglyceride levels and 1.39 (95% CI: 1.03 to 1.86) for only greater waist circumference. The association between HTGW and hyperuricemia was more prominent among females  than males , with evidence of a multiplicative interaction (Middle-aged and older females with the HTGW phenotype may at the highest risk of hyperuricemia. Future hyperuricemia prevention interventions should be primarily targeted for females with the HTGW phenotype.The online version contains supplementary material available at 10.1186/s12944-023-01795-2. Hyperuricemia is a metabolic disease caused by excessive production of uric acid or reduced renal excretion and is usually defined as a condition where the level of uric acid exceeds the normal range , 2. PrevPrevious studies reported that elevated triglycerides and enlarged waist circumference were associated with a higher risk of hyperuricemia , 8. The It is worth noting that sex differences in relation to metabolic syndrome components are common, especially among adults 45 years and older . For exaIn this study, we used 5562 participants from the China Health and Retirement Longitudinal Study (CHARLS) to examine the prospective relationship between the HTGW phenotype and hyperuricemia among middle-aged and older adults. An HTGW phenotype-sex interaction was also investigated.n = 1732); 2) had missing information on triglycerides (n = 10), uric acid (n = 3), waist circumference (n = 1524) and both triglycerides and uric acid (n = 5567); 3) were lost or refused to follow-up (n = 2926); and 4) had no information on uric acid in 2015 (n = 13), 5562 participants remained in the analytical sample.The data were obtained from the China Health and Retirement Longitudinal Study (CHARLS), a nationally representative cohort survey consisting of community residents aged 45 years or older. Initial samples were recruited from 2011 by multistage probability sampling and followed up every 2 years. Questionnaire surveys and physical measurements are conducted at every follow-up, and blood sample collection is performed once every two follow-up cycles , 19. In Fasting venous blood samples were collected from participants and tested at the Clinical Laboratory of Capital Medical University in 2011 and 2015 . Triglyc2) and categorized as underweight (< 18.5 kg/m2), normal weight (18.5–23.9 kg/m2), overweight (24–27.9 kg/m2) and obese (≥ 28 kg/m2), according to the revised Asia-Pacific BMI criteria by the World Health Organization [Covariates were collected at baseline mainly through standardized questionnaires and anthropometric measurements. Maximum years of schooling , marital status , residential location , smoking (current smokers vs. current nonsmokers), alcohol consumption  were dichotomized. Body mass index (BMI) was calculated by dividing weight (kg) by the square of height  and one-way ANOVA were used for categorical variables and continuous variables, respectively. We also compared the characteristics of those with and without information on triglycerides and waist circumference. Multivariate logistic regression models were performed to detect the associations between the triglyceride-waist phenotypes and hyperuricemia after adjusting for age, sex, education, marital status, residential location, smoking, alcohol consumption, BMI, and health status. Furthermore, the joint effect of the HTGW phenotype and sex on hyperuricemia was quantified, and the two-way multiplicative interaction was examined.To test the differences in characteristics between participants with different hyperuricemia statuses, chi-square  adjusting the treatment of dyslipidemia as a confounder; 2) people with treatment of dyslipidemia were excluded, and then the main analysis was repeated.All analyses were performed using Stata 16.0 . Odds ratios (ORs) and 95% confidence intervals (CIs) were used to describe the associations.All interviewees were required to sign the informed consent form, and the data collection of CHARLS was approved by the Biomedical Ethics Review Committee of Peking University (IRB00001052–11015).Table After the four-year follow-up, 549 (9.9%) incident hyperuricemia cases were ascertained. In the fully adjusted model, participants with the NTGW , HTNW , and HTGW  phenotypes had significantly higher hyperuricemia incidence than those with the NTNW phenotype (Table P < 0.001) but not in males  (Table two-way multiplicative = 0.006) was observed, which suggests that females with the HTGW phenotype had a 1.41-fold (95% CI: 1.05 to 1.91) higher risk of hyperuricemia than males with non-HTGW conditions  were associated with a higher risk of hyperuricemia among middle-aged and older adults. In addition, female sex and the HTGW phenotype interact in their relationship with hyperuricemia, suggesting that the HTGW phenotype was associated with a much higher odds of hyperuricemia in females but not in males.In our study, the incidence proportion of hyperuricemia was 9.9% after a four-year follow-up, which was comparable with a longitudinal study using the same database  . The posFurthermore, the present study showed that the association between the HTGW phenotype and hyperuricemia was modified by sex, with females experiencing the highest risk. This is consistent with a prospective study that considered the triglyceride-glucose index (Tyg) (a marker of insulin resistance) as a better index of hyperuricemia in females  than in males  . However2 (without adjusting BMI), the model3 (fully adjusted model) experienced a 23.0% attenuation of the effects from 1.82 (95% CI: 1.36 to 2.42) in model2 to 1.41 (95% CI: 1.05 to 1.91) in model3, this might support aforementioned pathway  for triglycerides and waist circumference, which may lead to selection bias, as healthy individuals seemed to contribute more to these missing values. However, the results remained similar in the sensitivity analyses when missing values were replaced by imputation. We have also adjusted, e.g., health status into the model to minimize this selection bias. Third, several variables that would have better explained the association between the HTGW phenotype and hyperuricemia, such as diet, genetics, sex hormone levels, and menopausal status of females, were not available in this dataset.The current study has several strengths, including the use of nationally representative data with a large cohort sample size and objective measures of exposures and outcome indicators. The use of longitudinal design minimize the chance of reverse causation. Nevertheless, some limitations should be considered. First, waist circumference and triglyceride levels were only measured at baseline, which prevented assessment of their impact on hyperuricemia over time, resulting in a potential underestimation of the association. Second, there were substantial missing values (In summary, females with the HTGW phenotype were more likely to suffer from hyperuricemia among middle-aged and older adults. Future interventions to prevent hyperuricemia should target females with both enlarged waist circumference and elevated triglyceride levels.Additional file 1.


In addition, we analyzed the correlation between gut microbiota dysbiosis and immune indicators, and evaluated the clinical discriminatory power of discovered bacterial biomarkers. We found that children with sepsis exhibited gut bacterial dysbiosis and low alpha diversity. The Spearman’s rank correlation coefficient suggested that Rhodococcus erythropolis had a significantly positive correlation with IFN-γ and CD3+ T cells. Klebsiella pneumoniae and Streptococcus mitis were significantly correlated with NK cells. Bacteroides uniformis was significantly positively correlated with IgM and erythrocyte sedimentation rate, and Eubacterium eligens was significantly positively correlated with IL-4 and CD3+CD8+ T cells. The biomarkers discovered in this study had strong discriminatory power. These changes in the gut microbiome may be closely related to immunologic dysfunction and to the development or exacerbation of sepsis. However, a large sample size is required for verification.Sepsis is a life-threatening multiple-organ injury caused by disordered host immune response to microbial infection. However, the correlation between gut microbiota dysbiosis and immune indicators remains unexplored. To address this gap in knowledge, we carried out 16 S rDNA sequencing, analyzed clinical fecal samples from children with sepsis (n = 30) and control children (n = 25), and obtained immune indicators, including T cell subtypes (CD3The online version contains supplementary material available at 10.1186/s12887-023-04349-8. Sepsis, a dysregulated immune response to infection resulting in multi-organ damage and even death, is a major public health threat that affects ∼1.2 million children worldwide each year . DespiteThe gut microbiota significantly regulates the development and functions of innate and adaptive immune systems , and gutStaphylococcus spp, Klebsiella pneumoniae, and Escherichia coli, which are translocated and cause bacteremia [+ T cell response [Proteobacteria-rich microbiota resulted in T cell-dependent increases in serum immunoglobulin (Ig) A levels and provided protection against polymicrobial sepsis [Some 16 S rRNA gene sequencing results have indicated that patients with sepsis have low gut microbiome diversity and high relative abundance of pathogenic bacteria, such as cteremia . Gloria cteremia  found thl sepsis . The murl sepsis , 19. AddTo investigate this issue, we performed 16 S rDNA sequencing to explore changes in the composition of the gut microbiota and performed analysis to find correlations between the gut microbiota and immune indicators for children with sepsis. The aim of this study was to provide a possible reference for the diagnosis and treatment of sepsis in children.A total of 30 children with sepsis were recruited from the pediatric intensive care unit (PICU) in a Children’s Hospital Affiliated to Shandong University from December 2020 to December 2021. The inclusion criteria were as follows: (1) children with sepsis was diagnosed according to the International Consensus Conference on Pediatric Sepsis [Pediatric sepsis was defined the systemic inflammatory response syndrome in the presence of suspected or proven infection. The presence of at least two of the following four criteria, one of which must be abnormal temperature or leukocyte count: (1) Core temperature of > 38.5 °C or < 36 °C; (2) Tachycardia, defined as a mean heart rate > 2 SD above normal for age in the absence of external stimulus, chronic drugs, or painful stimuli; or otherwise unexplained persistent elevation over a 0.5- to 4-h time period OR for children < 1 year old: bradycardia, defined as a mean heart rate < 10 th percentile for age in the absence of external vagal stimulus, β-blocker drugs, or congenital heart disease; or otherwise unexplained persistent depression over a 0.5-h time period; (3) Mean respiratory rate > 2 SD above normal for age or mechanical ventilation for an acute process not related to underlying neuromuscular disease or the receipt of general anesthesia; (4) Leukocyte count elevated or depressed for age (not secondary to chemotherapy-induced leukopenia) or > 10% immature neutrophils.Twenty-five healthy children were included in this study as controls, who matched the children with sepsis in terms of age and sex. The exclusion criteria: (1) the history of septic infection; (2) antibiotics and/or probiotics within 3 months before enrolling; (3) gastrointestinal problem or any other disease; (4) developmental defects. The study protocol was maintained in accordance with the Declaration of Helsinki and was approved by the ethics committee of Children’s Hospital Affiliated to Shandong University . Written informed consent and questionnaires were obtained from the children’s parents.Fecal samples were collected from each participant and stored at − 80 °C before analysis and 250 mg of stool was preserved in a sterile 2 ml tube .http://www.biosino.org/node) with the accession number OEP003851.Total DNA extraction from fecal samples  was performed using a Fast DNA SPIN kit for feces  according to the manufacturer’s instructions. The V3–V4 hypervariable region was amplified with a universal primer pair 341 F (5′-CCTACGGGNGGCWGCAG-3′) and 805R (5′-GACTACHVGGGTATCTAATCC-3′) . Sequenchttps://ccb.jhu.edu/software/fqtrim/index.shtml), we obtained high-quality clean tags through the quality filtering of the raw reads under specific conditions. Chimeric sequences were filtered using V search software (v2.3.4) [Samples were sequenced on an Illumina NovaSeq platform according to the manufacturer’s recommendations. We assigned paired-end reads was assigned to samples according to their unique barcodes, and truncated the reads by cutting off the barcodes and primer sequences. The paired-end reads were merged using FLASH . Using f(v2.3.4) . In brie(v2.3.4) . After d(v2.3.4) .https://qiime2.org). the difference of microbial composition was further characterized by beta diversity and the data were shown as a principal coordinate analysis (PCoA) calculated by QIIME2 [www.arb-silva.de) for each representative sequences. Linear discriminant analysis effect size was introduced for the identification of bacterial biomarkers between children with sepsis and children in the control group [http://huttenhower.sph.harvard.edu/galaxy), and nonparametric factorial Kruskal–Wallis rank-sum test was performed, followed by the linear discriminant analysis (LDA) coupled with measurements, for the assessment of the effect size of each differentially abundant taxon [The indexes of Alpha diversity  were compared using Mann-Whitney U test at the ASV level . All indy QIIME2 . All weiy QIIME2 . The feaol group . This prnt taxon . The thrnt taxon . Other dThe ability of microbial markers to differentiate between children with sepsis and children in the control was evaluated using the area under the receiver operating characteristic (ROC) curve . We sele+, CD3+CD4+, CD3+CD8+, and CD4/CD8), B lymphocyte (BLC), NK cells, IgA, IgM, IgG, and cytokines . Serum T-cell subtypes  and NK cells were assessed by flow cytometry. IL-2, IL-4, IL-6, IL-10, TNF-α, and interferon (IFN)-γ levels were quantified by adopting immunoluminescence method.The association of the taxonomic composition of gut microbiota with sepsis and clinical parameters was assessed. The clinical parameters were collected and determined at the clinical laboratory of Children’s Hospital Affiliated to Shandong University. The clinical indices, including hospital length of stay, white blood cell (WBC), erythrocyte sedimentation rate (ESR), neutrophil cell (NC), C-reactive protein (CRP), procalcitonin (PCT), organ damage number (ODN), T cell subtypes . We conducted two-tailed t-tests to compare demographics (nonparametric test), a two-tailed significance level of We enrolled 30 children with sepsis  and 25 matched typically developing children without sepsis  in the current study. The average age of children in the sepsis and control groups at the time of sample collection was 3.15  and 4.016 , respectively.This study obtained 2,942,246 high-quality reads and classification at an average of 53,495 reads per sample. At 100% similarity level, this study identified 11,821 ASVs in all samples and an average of 215 ASVs per sample.p = 0.00; Shannon index 5.77 vs. 2.89, p = 0.00; observed species index 282.32 vs. 155.53, p = 0.00) . At the phylum level, significant decrease in the relative abundance of Firmicutes and Bacteroidetes, and increase in Actinobacteria and Proteobacteria were observed in the sepsis group compared with the control group , which might be explained by immediate sampling of stool at the beginning of the sepsis , several clinical immunological indices and other clinical indices . All of the selected bacterial species with ROC curve (AUC) values were higher than 0.7. The discovered bacterial species with significant correlation with clinical immunological indices may have potential value in diagnosis and risk assessment (Fig. To calculate the diagnostic accuracy of bacterial biomarkers, we selected nine biomarkers of the bacterial taxa at the species level. The nine biomarkers had significantly correlation with clinical immunological indices. Out of the nine bacterial species tested, ent Fig. .Klebsiella pneumonia, Streptococcus constellatus, and Stenotrophomonas maltophilia. At the genus level, the pathogen identified by blood culture were all concordant with ASVs detected in the gut microbiota from the children with sepsis. Notably, The pathogen S. maltophilia identified by blood culture was the most abundant ASVs in the gut microbiome the most abundant at species and genus levels in case 28.7/30 children with sepsis had blood culture-proven sepsis with exclusively single pathogen detection. The blood culture positive cases of the children with sepsis and the corresponding reads in the sequencing data of the stool samples (Additional file 1: Table Sepsis is a heterogeneous and multifaceted dysregulation of the host response to an infecting pathogen in the presence of organ dysfunction , 37. ThiEnterococcus, Klebsiella, and Streptococcus, and significant reduction in B. uniformis and Faecalibacterium were observed in the sepsis group compared with the control group. The perturbation of the gut microbiome increased bacterial dissemination and might induce or exacerbate systemic inflammation and organ failure [S. maltophilia and was also isolated in blood culture, supporting previously proposed to increase sepsis risk originating from the gut translocation [Our findings showed that the structures in the gut microbiome significantly differ between children with sepsis and those without sepsis. Alpha diversity based on Shannon, observed species, and Chao1 indices were significantly reduced in children with sepsis compared with the controls, consistent with the results of Zhanguo Liu et al.  and Jing failure . Noteworlocation .R. erythropolis in children with sepsis significantly increased. R. erythropolis can cause bloodstream infection and is associated with HIV immunodeficiency [R. erythropolis had a significantly positive correlation with IFN-γ and CD3+ T cells and a significantly negative correlation with BLC. IFN-γ plays an important role in the pathogenesis of sepsis and exhibits a significantly high plasma levels in patients with sepsis [R. erythropolis,γ is a risk factor for sepsis and targeting R. erythropolis may provide an efficient therapy for sepsis.Notably, the relative abundance of ficiency , 47. Thih sepsis , 49. IFNh sepsis . We propK. pneumoniae and S. mitis from the fecal samples of the children with sepsis was significantly correlated with NK cells. Previous research conducted on mouse models indicated that NK cells play a vital role in systemic inflammation [K. pneumoniae and S. mitis from the gut microbiota dysbiosis are closely associated with excessive NK cell activation and IFN-γ production.Surprisingly, a high abundance of pathogenic bacteria ammation . Excessiammation , 51. TheB. uniformis and E. eligens were observed in children with sepsis, providing evidence of reduced fermentation capacity of probiotic bacteria. B. uniformis was significantly positively related with IgM and ESR. E. eligens was significantly positively correlated with IL-4 and CD3+CD8+ T cells. Panigrahi et al. reported a randomized, double-blind, and placebo-controlled trial of 4556 infants and showed that a synbiotic containing Lactobacillus plantarum can result in 40% relative risk reduction for low respiratory tract infections, death and effectively prevent neonatal sepsis [Considerably low abundance of l sepsis . Studiesl sepsis , 54. ProOur study provided evidence that the profitable bacteria are closely related to clinical immunological indices. It can be concluded that administration of probiotics may have a beneficial effect that alleviates sepsis by reducing symptom severity and morbidity through immune homeostasis regulation. However, the main side effects of probiotics are related to bacteremia/fungemia, with predilection found in premature newborns, elderly, immunosuppressed or critically ill patients with severe or fatal comorbidities, or patients in intensive care units treated with broad-spectrum antibiotics on central venous catheters . Thus, tIn the current study, the AUC values of the discovered bacterial species, which had significant correlation with clinical immunological indices, were higher than 0.7. The identified bacterial biomarkers exhibited remarkable discriminatory power for differentiating children with sepsis from healthy control children, demonstrating diagnosis and predictive power for sepsis.Several important limitations of this study should be highlighted. First, the sample size was small. This study included the children with sepsis hospitalized in only one center. Especially, the gut bacteria biomarkers were required validation in further studies with large multi-center samples. Furthermore, it is necessary to determine the correlation between the metabolites of the gut bacteria and sepsis using multi-omics approach. Finally, the role of intestinal pathogenic bacteria in sepsis were only using correlation analysis in this study. The further studies need to be conducted in cell and animal experiments to identify the causal relationship between gut microbiota and sepsis.In summary, we provided unprecedented evidence of the close correlation between disordered gut microbiota and blood immune indicators. Gut microbiota dysbiosis may be an important target for sepsis prevention and therapy. Furthermore, we demonstrated that intestinal bacteria associated with immune indicators are highly sensitive and specific markers that can be used in distinguishing between children with sepsis and healthy children. The discriminatory power of these candidate biomarkers paves the way for establishing fecal microbiome tests for clinical diagnostic and prognostic screening of sepsis. However, a large sample size is required for verification.Below is the link to the electronic supplementary material.Additional file 1 Table 1: The damaged organs and bacterial isolation in the blood culture of all children with sepsisAdditional file 2 Table 2: Organ damage influencing the gut microbiome of children with sepsis


Disulfidptosis is a newly identified variant of cell death characterized by disulfide accumulation, which is independent of ATP depletion. Accordingly, the latent influence of disulfidptosis on the prognosis of lung adenocarcinoma (LUAD) patients and the progression of tumors remains poorly understood.We conducted a multifaceted analysis of the transcriptional and genetic modifications in disulfidptosis regulators (DRs) specific to LUAD, followed by an evaluation of their expression configurations to define DR clusters. Harnessing the differentially expressed genes (DEGs) identified from these clusters, we formulated an optimal predictive model by amalgamating 10 distinct machine learning algorithms across 101 unique combinations to compute the disulfidptosis score (DS). Patients were subsequently stratified into high and low DS cohorts based on median DS values. We then performed an exhaustive comparison between these cohorts, focusing on somatic mutations, clinical attributes, tumor microenvironment, and treatment responsiveness. Finally, we empirically validated the biological implications of a critical gene, KYNU, through assays in LUAD cell lines.We identified two DR clusters and there were great differences in overall survival (OS) and tumor microenvironment. We selected the "Least Absolute Shrinkage and Selection Operator (LASSO) + Random Survival Forest (RFS)" algorithm to develop a DS based on the average C-index across different cohorts. Our model effectively stratified LUAD patients into high- and low-DS subgroups, with this latter demonstrating superior OS, a reduced mutational landscape, enhanced immune status, and increased sensitivity to immunotherapy. Notably, the predictive accuracy of DS outperformed the published LUAD signature and clinical features. Finally, we validated the DS expression using clinical samples and found that inhibiting KYNU suppressed LUAD cells proliferation, invasiveness, and migration in vitro.The DR-based scoring system that we developed enabled accurate prognostic stratification of LUAD patients and provides important insights into the molecular mechanisms and treatment strategies for LUAD. Lung cancer is a global health concern and one of the foremost sources of cancer patient morbidity and mortality, posing a grave threat to public health . In 2020Programmed cell death (PCD) is a cellular death process governed by a molecular program that is controlled by particular genes. This process is essential for the normal development of organisms and the preservation of homeostasis . ExploraIn the current study, we divided 1569 LUAD samples into two disulfidptosis-associated subtypes according to 18 DRs and compared survival and immune infiltration between the subtypes. We also developed a disulfidptosis score (DS) to predict overall survival (OS) and to delineate the immunological landscape of LUAD. As indicated by the findings, a higher DS was associated with unfavorable prognostic outcomes and worse immunotherapy responses in LUAD, suggesting the potential clinical utility of DS as a tool for assessing prognosis and immunotherapy efficacy. Thus, the current study introduces an innovative approach for assessing the efficacy of immunotherapy and predicting the prognosis of LUAD patients based on DS.https://portal.gdc.cancer.gov/), GSE31210, GSE68465, and GSE72094 in Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/), which included RNA sequencing data, somatic mutation data, copy number variation (CNV) data, and corresponding clinical information. The TCGA-LUAD cohort, which consisted of 539 LUAD tissues and 59 cancer-adjacent tissue samples, served as a training cohort. Meanwhile, GSE31210, GSE68465, and GSE72094 were utilized for the validation cohort, which consisted of 1,150 LUAD patients. Additionally, the “sva” package was used to correct the batch effect between the different datasets by adopting the “combat” algorithm (The LUAD data were obtained from The Cancer Genome Atlas (TCGA)-LUAD  and their stability  were determined by the consensus clustering algorithm (DEGs among DRs subtypes were determined using the “limma” R package with the filtering criteria of log (fold change) >1 and False-discovery rate (FDR) <0.05 . To furtThe DS was calculated to quantify the disulfidptosis patterns of the LUAD. Accordingly, a univariate cox regression analysis was conducted to identify the DEGs are related to prognosis. Subsequently, the patients were segregated into distinct gene cluster groups according to the expression of prognostic DEGs using the unsupervised clustering method. Based on prognostic DEGs, the 10 machine learning algorithms, including ‘Least Absolute Shrinkage and Selection Operator ’, ‘Ridge (“glmnet” package)’, ‘Elastic network (“glmnet” package)’, ‘StepCox ’, ‘Survival support vector machine ’, ‘CoxBoost (“CoxBoost” package)’ , ‘SupervThe “maftools” package was utilized to evaluate and visualize the mutation type and frequency of the genes . Corresphttps://cistrome.shinyapps.io/timer/), and “MCPcounter” were used to quantify the relative infiltration of immune cells in the entire cohort (http://biocc.hrbmu.edu.cn/TIP/)  . In the cn/TIP/) . Meanwhicn/TIP/) . The “h.http://tide.dfci.harvard.edu/) score; additionally, the submap algorithm was applied to compare the efficacy of immunotherapy among various DS subtypes  and Profiling Relative Inhibition Simultaneously in Mixtures . The more sensitive a cell line is to a potential drug, the lower its area under the curve (AUC).To explore the predictive value of DS in LUAD patients after immunotherapy, we compared the immune dysfunction and exclusion . To construct KYNU knockdown and negative control (NC) cell lines, H838 and PC-9 cells were seeded in 6-well plates at a density of 5 × 104 cells/well and transfected with 50 nM siRNAs-KYNU and siRNA negative control (siRNA-NC) using lipofectamine 3000  following the manufacturer’s guidelines . After 48 h of transfection, subsequent experiments were conducted . The siRNA sequences are provided in Two human LUAD cells (PC-9 and H838) as well as a normal bronchial epithelial cell (BEAS-2B) were obtained from the American Type Culture Collection . The PC-9 and H838 cells were grown in RPMI 1640 supplemented with 10% FBS and 1% penicillin-streptomycin, while BEAS-2B cells were grown in DMEM supplemented with 10% FBS and 1% penicillin-streptomycin in humidified air at 37°C and 5% COFor this study, a total of 15 TM tissue samples (HLugA030PG04-1) were utilized, including 15 LUAD and 15 adjacent non-tumor tissues. All the tissues were procured from Shanghai Outdo Biotech Co., Ltd. . TM was stained using IHC with KYNU. In brief, the antibodies were diluted to the suitable concentration and incubated overnight with the sections at 4°C. The avidin–biotin and streptavidin complex were then incubated with the biotinylated goat anti-rabbit IgG secondary antibody for 0.5 h. The cell nuclei were counterstained blue with Hematoxylin. Each specimen was graded based on the intensity  and the proportion of positively stained cells . The final IHC scores were then calculated as the product of the intensity score and the percentage score .® 480II System). The relative gene expression was normalized to β-actin, acting as the control gene. The primer sequences for the genes are outlined in −ΔΔCt method.RNA extraction was performed employing RNA extraction kit  in accordance with the manufacturer’s instructions. The complementary DNA (cDNA) was synthesized from total RNA for each sample by using a reverse transcription kit . Subsequently, the mRNA expression was quantitatively analyzed via RT-PCR  was added to each well for 2 h at 37°C. Subsequently, the absorbance values of each well were measured at 450 nm. For colony formation assay, 500 cells were seeded into each well of a 12-well plate and incubated. After 10 days, the cells were stained with crystal violet solution, and fixed with 4% paraformaldehyde for 0.5 h. Finally, colonies consisting of more than 50 cells were counted.4 cells were resuspended in 200 μl serum-free medium and placed to the upper chamber. The lower chamber was filled with 700 μl of medium containing 10% FBS. After 18 h, cells that migrated through the membrane were fixed and stained with hematoxylin. Following a 24 h-incubation period, cells that traversed the membrane were fixed with 4% paraformaldehyde for 30 minutes and stained with a crystal violet solution for 15 min. Subsequently, they were observed with a microscope, and five random fields of view were selected to count the cells. The protocol for the invasion assay was similar to the migration assay, with the exception that the upper chambers were coated with 70 μl of diluted Matrigel. In addition, the wound healing assay was utilized to examine cell migration. Serum-starved LUAD cells (2 × 105) were seeded in 6 well plates and then transfected with siRNA-NC or siRNA-KYNU. Upon reaching >95% cell confluence, a sterile 20 μl pipette tip was used to create a scratch in the monolayer of cells. After a PBS wash, the cells were incubated for 0 and 24 h in the corresponding basic culture medium. The monolayer cells were examined microscopically, and the gap distance was measured quantitatively to ascertain LUAD cell migration.The transwell experiment was executed using a transwell chamber . For migration assays, a total of 4 × 10All statistical analyses and representations were conducted using R (version 4.2.1) and GraphPad Prism (version 9.00). The Chi-squared test was used to compare the proportion of individuals within two groups. Additionally, continuous variables in two or more groups were compared using Wilcoxon rank-sum test or Kruskal–Walli’s test. For correlation analysis, the Pearson correlation test was employed. A p-value less than 0.05 was deemed statistically significant.Gene expression analysis using bulk RNA-seq demonstrated that the majority of DRs displayed relative higher expression levels in LUAD tissues compared to para-carcinoma tissues  curve was employed to assess the validity of DS, as the AUC value for TCGA (0.93–0.96), GSE31210 (0.68–0.79), GSE68465 (0.63–0.66), GSE72094 (0.63–0.72), and meta-cohort (0.71–0.78) 4. In or). Comparing the frequency of mutants between the high- and low-DS groups, more somatic mutations, both synonymous and nonsynonymous, were observed in the high-DS group  clustering algorithm  can be found in the article/The studies involving humans were approved by Ethics Committee and Institutional Review Board of the Outdo Biotech. Co., Ltd. (SHYJS-CP-2210035). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.CY and YZ conceived and designed the study. CL and YW performed the collection and assembly of data. YX and CL analyzed the data. YZ and YW performed experiments and wrote the manuscript. All authors read and approved the final manuscript.


Respiratory syncytial virus (RSV) is the most common cause of bronchiolitis and is related to the severity of the disease. This study aimed to develop and validate a nomogram for predicting severe bronchiolitis in infants and young children with RSV infection.A total of 325 children with RSV-associated bronchiolitis were enrolled, including 125 severe cases and 200 mild cases. A prediction model was built on 227 cases and validated on 98 cases, which were divided by random sampling in R software. Relevant clinical, laboratory and imaging data were collected. Multivariate logistic regression models were used to determine optimal predictors and to construct nomograms. The performance of the nomogram was evaluated by the area under the characteristic curve (AUC), calibration ability and decision curve analysis (DCA).n = 227) and 63 (64.3%) mild and 35 (35.7%) severe cases in the validation group (n = 98). Multivariate logistic regression analysis identified 5 variables as significant predictive factors to construct the nomogram for predicting severe RSV-associated bronchiolitis, including preterm birth , weight at admission , breathing rate , lymphocyte percentage  and outpatient use of glucocorticoids . The AUC value of the nomogram was 0.784  in the training set and 0.832  in the validation set, which showed a good fit. The calibration plot and Hosmer‒Lemeshow test indicated that the predicted probability had good consistency with the actual probability both in the training group (P = 0.817) and validation group (P = 0.290). The DCA curve shows that the nomogram has good clinical value.There were 137 (60.4%) mild and 90 (39.6%) severe RSV-associated bronchiolitis cases in the training group (A nomogram for predicting severe RSV-associated bronchiolitis in the early clinical stage was established and validated, which can help physicians identify severe RSV-associated bronchiolitis and then choose reasonable treatment. Children with bronchiolitis accounted for 12.25–21.24% of the total number of hospitalised patients with respiratory tract infections at the First Hospital of Jilin University in China between January 2005 and December 2014, with an average hospital stay duration of 7.78 ± 3.47 days [Bronchiolitis is a lower respiratory tract disease usually caused by respiratory virus infection in infants and young children , 2. It i.47 days .Respiratory syncytial virus (RSV) is the most common cause of bronchiolitis, accounting for 41–83% of all patients with bronchiolitis . MoreoveA retrospective study was conducted in 325 patients with RSV-associated bronchiolitis who were hospitalized at Tianjin Children's Hospital in China from January 2018 to December 2021. This study was approved by the ethics committee of the Tianjin Children’s Hospital and conducted in accordance with the Declaration of Helsinki guidelines.The following three inclusion criteria were met by all the children enrolled in this study: (1) age < 2 years, which was consistent with the diagnostic criteria of the American Academy of Pediatrics (AAP) Guidelines in 2014 and the National Institute for Health and Care Excellence (NICE) Guidelines in 2021 for the Clinical Diagnosis of bronchiolitis , 23; (2)Severe bronchiolitis was diagnosed according to the expert consensus on the diagnosis, treatment and prevention of bronchiolitis (2014 edition) , any of The exclusion criteria included any of the following: (1) a course of illness for more than 2 weeks when admitted to the hospital; (2) nosocomial infection; (3) automatic discharge or death during hospitalization; (4) co-bacterial infection; or (5) incomplete medical records.All the patients’ medical data were collected at hospital admission and discharge, including demographic information, medical history, physical examination, etiological examination, laboratory data, imaging features and clinical management, as follows: (1) demographic information: age, gender, region , weight at admission, preterm birth, mode of delivery , history of birth asphyxia, birth weight, feeding mode (breast/formula feeding), underlying diseases , history of wheezing, history of eczema; (2) medical history and physical examination: fever, cough and wheezing days before admission, use of antibiotics and systemic corticosteroids before admission, breath rate, three concave signs , abnormal lung auscultation ; (3) etiological examination: the nasopharyngeal secretions of the children were collected on admission, and a viral nucleic acid extraction kit produced by Hubei Langde Medical Technology Limited Company was used to extract viral RNA. Then, PCR amplification was performed to detect 7 respiratory pathogen nucleic acids . Two sputum samples and one blood sample were collected simultaneously for Gram staining and culturing in growth medium to exclude bacterial infection and galactomannan by antigen assay to exclude fungal infection; (4) lung X-ray examination ; (5) laboratory data: white blood cell (WBC), neutrophil ratio (N%), lymphocyte ratio (L%), eosinophil ratio (E%), hemoglobin (Hb), C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), lactic acid (La), aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatine kinase (CK), creatine kinase isomer-MB (CK-MB), lactic dehydrogenase (LDH), immunoglobulin E (IgE); (6) hospital course: hospitalization days.P < 0.1) at univariate analysis were included in the multivariable model.We used R software with the “sample ” function to randomly divide the data of the 325 patients into a training group  and a validation group . All 227 patients in the training dataset were analysed for variable selection and risk prediction. Variables significant , and the calibration plot accompanied by the Hosmer‒Lemeshow test was applied to assess the calibration ability. The model was validated using the bootstrap method with 1000 resamples to quantify any overfitting. Decision curve analysis (DCA) was applied to evaluate the clinical utility of the nomogram based on its net benefits at different threshold probabilities.In addition, for better clinical application of the nomogram, the total scores of each patient were calculated based on the model. The ROC analysis was used to explore the optimal cutoff value for predicting severe RSV-associated bronchiolitis, and the critical value with maximum Youden index (sensitivity + specificity-1) was determined. Accuracy of the optimal cutoff value was assessed by the sensitivity and specificity.http://www.r-project.org) was used to perform all the graphics based on the R packages “foreign”, “rms”, “ggplot2”, “pROC” and “glmnet”. P < 0.05 was considered statistically significant, and factors with P < 0.1 in the univariate analysis were included in multivariate logistic regression analysis.Continuous variables were expressed as the mean ± standard deviation (SD) or median values (interquartile range) and assessed by independent group t tests or Mann‒Whitney U tests. Categorical variables were expressed as percentages (%) and assessed by Chi-squared tests or Fisher’s exact test. Statistical analysis was carried out using SPSS 26.0, and R software  and a validation group (n = 98). There were 90 (39.6%) and 35 (35.7%) patients with severe RSV infection in the training and validation groups, respectively. The baseline clinical data and proportion of severe RSV infection were similar between the training and validation groups, except for serum AST level and length of wheezing  were male, and 125 cases were diagnosed as severe RSV infection. The data were randomly divided into a training group (P < 0.001), lower median weight at admission , higher proportion of country , higher preterm birth rate , higher cesarean section rate , higher incidence of underlying disease , faster median respiratory rate , higher three concave signs rate , longer median duration of hospital , lower mean level of Hb , median IgE , higher median level of CK , CKMB  and LDH  compared with those mild RSV infection , weight at admission , children from rural areas , preterm birth , cesarean section , fever history , breathing rate , level of CKMB  and LDH  were significant predictors of severe RSV-associated bronchiolitis , preterm birth , faster breathing rate , outpatient use of glucocorticoids  and lymphocyte percentage  were independent predictors for severe RSV-associated bronchiolitis  of the prediction model showed good consistency between the predicted probability and actual probability.By internal bootstrap validation with 1000 resamples, the mean AUC of the nomogram based on the training group was 0.784  Fig. A and HosP = 0.290) showed that the prediction model fit well in the validation dataset. The DCA curve showed obvious net benefits of the predictive nomogram and was significantly higher than those of the two extreme cases  , preterm birth of no (0 point), lymphocyte percentage of 40% (37 points), breathing rate of 40 (50 points) and outpatient use of glucocorticoids is yes (23 points), the probability of severe RSV infection is estimated to be 78%. The predictive model is easy to operate and helpful for the early identification and timely treatment of high-risk infants and young children with bronchiolitis.P = 0.000). Additionally, our study showed that preterm birth was closely associated with the severity of RSV-associated bronchiolitis. A possible explanation may be attributed to the fact that preterm birth interrupts normal lung development in utero, resulting in significant changes in the pulmonary physiology and function. In preterm babies, the true alveolar structure is not completely formed, their surfactant and cortisol systems are immature, and their foetal lung is not ready for gas exchange, making them more likely to develop severe respiratory diseases [Preterm birth is reported to be a significant risk factor for severe RSV-associated bronchiolitis , 25–27, diseases –31.P = 0.30). However, some studies have reported that early administration of oral dexamethasone in the treatment of patients with acute bronchiolitis can reduce the hospitalisation rates  in children aged < 24 months (P = 0.039) [Our findings revealed that children who received systemic glucocorticoids in an outpatient setting were 2.27 times more likely to develop severe RSV-associated bronchiolitis than those who did not. However, due to the controversial efficacy of inhaled or systemic glucocorticoids in acute bronchiolitis, the current expert consensus in China on the diagnosis and treatment of bronchiolitis recommends that  glucocor= 0.039) . The eff= 0.039) . This maP = 0.001), and our study provides data that support this argument from the perspective of the prediction model.In severe bronchiolitis, airway resistance shows a significant increase, with obstruction of the small airways due to mucus blockage and airway wall oedema as well as bronchospasm in the relatively narrow airways in infants, resulting in an increased breathing rate and work of breathing . Kohei eP = 0.819) between the RSV-mild group (8.6 ± 3.4 × 109/L) and the RSV-severe group (8.7 ± 3.2 × 109/L). However, the results of multivariate regression analysis showed that a decreased lymphocyte ratio (53.9 ± 15.7) was an independent risk factor for severe RSV infection . Paola et al. [P = 0.014) was an independent risk factor for severe bronchiolitis, which was consistent with our results. This may indicate an insufficient adaptive immune response in the infants and young children in the severe group. A previous study [In our findings, the white blood cell count was not significantly different . Our study also showed that a higher admission weight could lower the odds of severe cases . The weight of infants and young children shows a specific exponential relationship with their chronological age according to the WHO Child Growth Criteria [Malcolm et al.  reportedCriteria . FurtherCriteria , 31, 40.P > 0.05). We believe this might be related to the large age span of our study (0–2 years), while the age of the samples studied by Paola et al. [n = 325) and different races [. [P > 0.05), while in the study by Marcello et al. [In addition, Paola et al.  and Jonaa et al.  was withnt races , 41. Ourraces [.  and Jonao et al. , the livThis study has some limitations. Environmental factors, including air pollution  and tobacco smoke exposure, were not collected in the medical records. Previous studies reported that these factors increase the severity of RSV infections , 44. In In conclusion, we developed and validated a nomogram for predicting severe RSV-associated bronchiolitis in the early clinical stage, which is easy and convenient for the physicians to use.


Global climate change may lead to changes in precipitation patterns. This may have a significant impact on the microbial communities present in the soil. However, the way these communities respond to seasonal variations in precipitation, particularly in the context of increased precipitation amounts, is not yet well understood.To explore this issue, a five-year (2012–2016) field study was conducted at the northeast boundary of the Ulan Buh Desert, examining the effects of increased precipitation during different periods of the growing season on both bacterial and fungal communities. The study included five precipitation pattern treatments: a control group (C), as well as groups receiving 50 and 100% of the local mean annual precipitation amount (145 mm) during either the early growing season (E50 and E100) or the late growing season (L50 and L100). The taxonomic composition of the soil bacterial and fungal communities was analyzed using Illumina sequencing.After 5 years, the bacterial community composition had significantly changed in all treatment groups, with soil bacteria proving to be more sensitive to changes in precipitation timing than to increased precipitation amounts within the desert ecosystem. Specifically, the alpha diversity of bacterial communities in the late growing season plots (L50 and L100) decreased significantly, while no significant changes were observed in the early growing season plots (E50 and E100). In contrast, fungal community composition remained relatively stable in response to changes in precipitation patterns. Predictions of bacterial community function suggested that the potential functional taxa in the bacterial community associated with the cycling of carbon and nitrogen were significantly altered in the late growing season (L50 and L100).These findings emphasize the importance of precipitation timing in regulating microbial communities and ecosystem functions in arid regions experiencing increased precipitation amounts. ChangesThe desert ecosystem constitutes nearly one-third of the Earth’s land surface , and is Soil bacterial and fungal communities are important components in desert ecosystem . Since bPlant growth and primary productivity are known to be stimulated by increased precipitation amounts, as supported by various studies . HoweverNitraria tangutorum in this ecosystem, the entire growing season could be divided into two periods , and is managed by the Institute of Desertification Studies, Chinese Academy of Forestry. The soil types at the study site are sandy and gray-brown desert soil (Cambic Arenosols and Luvic Gypsisols in FAO taxonomy). The site has an arid continental climate with an average annual precipitation of 145 mm (1978–2007) and a temperature of 7.8°C. About 77.5% of the annual precipitation occurs between June and September. The average annual potential evapotranspiration is 2,327 mm .Nitraria tangutorum. The plant community develops on nabkhas (a sand dune that forms around plant).The plant type is temperate desert shrubs with 20–30% vegetation cover. The dominant plant species in this ecosystem is 2.2.Nitraria tangutorum, the entire growing season could be divided into two periods, early growing season  and late growing season , which were also designed for the two periods of precipitation increase  and ammonium (NH4+-N). The third part was air dried to measure soil pH, total carbon (TC), total nitrogen (TN) and total phosphorus (TP). Soil samples were acquired at the fifth year of the water adding experiment, portraying a cumulative 5-year response to sustained precipitation manipulation.Soil samples were collected 15 days after the last increase in precipitation during the growing season (25th September 2016). To estimate the average variation in soil microbial communities across nabkhas, soil samples were selected within bare patches with similar environmental conditions in all nabkhas to reduce the effect of plant root distribution. In addition, topsoil (0–20 cm depth) was randomly collected from five representative points (four corners and one center) in each experimental area using a 5-cm diameter drill. The augers were cleaned with sterile water and air dried before each sample. Soil samples from the same test area were pooled to obtain a composite soil sample. The composite soil samples were packed in polyethylene bags and immediately stored in containers with ice packs for transferring the samples to the laboratory at low temperatures. The composite soil samples were sieved through a 2 mm screen to remove visible roots, residues, and stones. The samples were then divided into three parts: the first part was stored at −80°C for soil DNA extraction; the second part was stored at 4°C for measurement of soil soluble inorganic nitrogen, including nitrate  was extracted using 2 mol L −1 KCl, and their contents were measured using continuous flow analytical system . The total carbon (TC) was measured by an elemental analyzer (FLASH 2000 CHNS/O), total nitrogen (TN) was determined by the Kjeldahl method, total phosphorus (TP) was measured by ammonium molybdate spectrophotometric method.Long-term soil temperature and soil moisture dynamics at 20 cm depth in four typical plots within each treatment were automatically monitored every 30 min by an EM50 data logger system , and values were averaged throughout the month. Soil pH was determined at a soil/water mass ratio of 1:2.5. Soil inorganic N  according to the manufacturer’s instructions, with the concentration (>100 ng μL−1) measured by a NanoDrop 2000 Spectrophotometer . The DNA purity of each sample was A260/A280 ratio between 1.8 and 2.0, and A260/A230 ratio greater than 1.5.Total DNA was extracted from 0.5 g sample of soil using an Ultra CleanTo assess the taxonomic profiles of bacterial communities, the V4 region of the 16S rRNA gene was sequenced using Illumina HiSeq2500 platform  at Novog2.6.Post hoc analyses were performed using Fisher’s least significant difference (LSD) test. Two-way ANOVA was used to examine the effects of increasing precipitation amount and time on microbial communities and environmental factors at the phyla, order, family, and genus levels. In order to comprehensively and extensively assess the influence of precipitation seasonality and amount on microbial taxa groups, we have selected the top 10 taxa at each taxonomic level as representatives, enabling a comparison of the diverse effects of precipitation on the microbial community. Normality of the data was verified using Shapiro–Wilk test. Bartlett’s test was used for homogeneity of variance test. Almost all the taxa group did not show normal distribution or conform to homogeneity of variance test. Thus, the nonparametric analysis, two-way permutational multivariate analysis of variance (PERMANOVA), was performed. Mantel test and spearman’s correlation coefficients were used to analyze the effects of plant/soil variables on the bacterial and fungal community compositions. Moreover, in order to further investigate the impact of environmental variables on microbial community diversity, we employed a random forest model to examine the correlations between bacterial and fungal diversities and environmental variables. All statistical analyses and figures described above were completed with R 4.0.0 (accessed on 10 April 2021)p-values by using the Benjamini and Hochberg false discovery rate (FDR) for multiple testing  and permutational multivariate analysis of variance (Adonis). The results were visualized using Nonmetric multidimensional scaling analysis (NMDS). One-way ANOVA was conducted to compare the effects of different precipitation treatments at the phyla, order, family, and genus levels.  testing . The pac testing . Package testing  was used testing  for gene3.3.1.3−-N) in the L100 plots was 1.5 times higher than that in the control plots, but no significant changes were observed in the other plots. The E100 and L100 plots had higher plant community cover than the other treatments, but due to the large coefficient of variation (4+-N) was below the detection limit in all treatments.Our results showed that different precipitation treatments had a significant impact on soil physicochemical properties in the desert ecosystem . Compareariation , the chap < 0.001) (p < 0.05) (3−-N content (p < 0.05) , different growing season periods (“precipitation season” hereafter), and their interactions (“interaction” hereafter) all had significant effects on soil moisture and soil temperature at 20 cm depth of soil (< 0.001) . Precipi < 0.05) . Precipi < 0.05) .3.2.R2 = 0.492, p = 0.001)   . Althoug= 0.001) , Adonis = 0.032) .p < 0.001 vs. precipitation amount: p > 0.006)  . On the Methylophilaceae, Methylobacteriaceae, Rhodobacteraceae whereas only the family of Bacillaceae decreased  and four of the ten most abundant genera , whereas precipitation amount had significant effects on only one family (Streptomycetaceae) and one genus (Microvirga) among most abundant taxa (The phyla of Proteobacteria (37.9%), Actinobacteria (38.0%), Firmicutes (6.4%), Acidobacteria (3.2%), Chloroflexi (3.5%), Gemmatimonadetes (3.0%), and Bacteroidetes (2.6%) were the dominant phyla in our site, making up over 90% of the total relative abundance . Specifiecreased . At the icrobium . Moreoveicrobium . Precipiant taxa . Thus, aant taxa .Trichocomaceae significantly decreases in L100 plots while only the family of Incertae sedis Hypocreales increased , whereas precipitation season had significant effects on only one genus (Stachybotrys) among most abundant taxa.The fungal group Ascomycota accounted for an overwhelming majority 84.3%), followed by Chytridiomycota (0.4%), Basidiomycota (0.6%), Zygomycota (0.3%), and Incertae sedis fungi (0.1%) . Approxi%, followncreased . At the Fusarium . MoreoveFusarium . Similar3.3.3−-N significantly correlated with the composition of soil bacterial and fungal communities, while other environmental factors exhibited no significant correlation . In contrast, moisture negatively correlated with the relative abundances of Acidobacteria , Chloroflexi  and Gemmatimonadetes  , while positively correlated with Chloroflexi   . Moreove < 0.05) . Regardi < 0.05) .3.4.p < 0.05) in the soil bacterial community. Specifically, the functions related to organic synthesis  were significantly enriched in the early growing season treatment plots  compared to control plots (p < 0.05) (p < 0.05) (p < 0.05) (p < 0.05)  . Convers < 0.05) . In addi < 0.05) . Convers < 0.05) . However < 0.05) .In order to make a more comprehensive prediction of potential functional taxa of bacterial communities, we also used PICRUSt2 software to predict bacterial communities, using the KEGG database comparison. The results of the comparison were 7,564 KOs, and functional proteins with average relative abundance less than 0.1% were filtered out, and 91 functional proteins were selected for the subsequent significance analysis. Finally, there were 39 functional proteins with significant changes . ConsistThe effects of precipitation season and precipitation amount on the potential functions of bacterial and fungal communities were further analyzed using a two-way PERMANOVA analysis . Our res4.Changes in precipitation patterns can alter the composition and abundance of belowground microbial communities . ConsistThere are two possible reasons for this finding. The first reason is the close association between bacterial community and the vegetation growth . A previThe second possible explanation for the relationship between bacterial diversity and the timing of increased precipitation is linked to the adaptation of the bacterial community to wet conditions over short time periods. Prior research has demonstrated that elevated levels of precipitation can boost soil microbial activity, but these effects tend to diminish as experiments proceed in arid and semi-arid regions . In our In addition, the observations that the alpha-diversity in the early growing season did not significantly change might attribute to two main reasons. First, the increased precipitation in the early growing season fostered plant growth and facilitated root development, consequently instigating bacterial proliferation. Nevertheless, this increase in precipitation also resulted in heightened water demands from the plants, consequently culminating in a discernible decline in soil moisture levels within the context of the early growing season treatment, precisely aligned with the juncture of soil sample collection at the denouement of the growing season  and moisture were the main factors shaping the community composition of bacteria and fungi  on 14 of the 22 potential functional groups, while precipitation increase amount had a significant effect (p < 0.05) on only five of these potential functional groups (p < 0.05). This may be due to the fact that temperature is significantly affected by the timing of the increase in precipitation (p < 0.001)  , whereas< 0.001) . In the < 0.001) . This sh< 0.001) , which p< 0.001) . Therefo5.3−-N content and soil total nitrogen content are the primary environmental factors influencing the structure of bacterial and fungal communities in desert soils. Two-way PERMANOVA analysis revealed that precipitation increase time had a greater impact on bacterial community alpha diversity and bacterial community composition compared to precipitation increase amount. Therefore, experiment settings involving a uniform increase or decrease in precipitation throughout the growing season may not accurately reflect the overall response patterns in these systems. Seasonal variation will play a critical role in the response of these communities, and precipitation increase time should be considered when we design future microbial community assessments in desert systems.In this study, we observed varying effects of the different timing of increased precipitation on the bacterial and fungal community structure of desert soils during the early and late growing season. The abundance and diversity of bacterial communities decreased significantly in response to precipitation increase treatment in the late growing season, whereas there were no significant effects on soil fungal community. The difference may be attributed to characteristics of plant development periods during the early and late growing season. Our findings suggest that soil moisture, soil NOThe datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/YG and BW: conceptualization and supervision. YG, XX, and FB: methodology. YX and KY: data analysis. YX: writing—original draft preparation and visualization. YG, XX, FB, JZ, and KY: writing—review and editing. BW: project administration. YG, BW, and JZ: funding acquisition. All authors have read and agreed to the published version of the manuscript.This work was financially supported by the National Natural Science Foundation of China , the Surplus Funds of Institute of Desertification Studies, CAF (Grant nos. IDS2018JY-3 and IDS2018JY-9), and Scientific Research Fund of Yunnan Provincial Department of Education (No. 2022J0512), Yunnan Province first-class disciplines forestry science discipline construction funds (523003), and Provision for the construction of first-class specialties in forestry science in Yunnan Province (523002).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. 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Pectinophora gossypiella) is one of the world’s most destructive pests of cotton. This invasive lepidopteran occurs in nearly all cotton-growing countries. Its presence in the Ord Valley of North West Australia poses a potential threat to the expanding cotton industry there. To assess this threat and better understand population structure of pink bollworm, we analysed genomic data from individuals collected in the field from North West Australia, India, and Pakistan, as well as from four laboratory colonies that originated in the United States. We identified single nucleotide polymorphisms (SNPs) using a reduced-representation, genotyping-by-sequencing technique (DArTseq). The final filtered dataset included 6355 SNPs and 88 individual genomes that clustered into five groups: Australia, India-Pakistan, and three groups from the United States. We also analysed sequences from Genbank for mitochondrial DNA (mtDNA) locus cytochrome c oxidase I (COI) for pink bollworm from six countries. We found low genetic diversity within populations and high differentiation between populations from different continents. The high genetic differentiation between Australia and the other populations and colonies sampled in this study reduces concerns about gene flow to North West Australia, particularly from populations in India and Pakistan that have evolved resistance to transgenic insecticidal cotton. We attribute the observed population structure to pink bollworm’s narrow host plant range and limited dispersal between continents.The pink bollworm ( Pink bollworm (Pectinophora gossypiella) is a major pest of cotton that has colonised more than 150 countries worldwide, including much of tropical America, Africa, Asia, and Australasia  has been grown in Australia since 1996 and has been effective against pink bollworm in the United States and China14. However, pink bollworm populations in India and Pakistan have evolved resistance to Bt cotton, with serious practical consequences15. In principle, connectivity among populations could result in the introduction of Bt-resistant pink bollworm into North West Australia. Thus, a greater understanding of pink bollworm population structure could be useful for assessing the threat to cotton in Australia, as well for improving surveillance and management elsewhere.In Australia, pink bollworm was first reported on cotton in Queensland in 192417. Two of these studies evaluated only the mitochondrial DNA (mtDNA) cytochrome c oxidase subunit I (COI) locus in samples from India17, two focused primarily on China and used two mtDNA loci 16 or 13 microsatellites5 respectively, and one was based on a piggyBac-like transposon insertion and its flanking sequences7. Of these, only the latter included populations from Australia. The conclusions from these studies were mixed, including apparently conflicting results from mtDNA and microsatellite DNA analysis of the same set of populations16. Population structure of pink bollworm has not been explored previously using genome-wide data that includes Australian samples and a large number of genetic markers. Such analysis may provide increased accuracy and resolution to address these discrepancies.Five previous studies of population structure in pink bollworm have analysed genetic variation based on DNA sequences from one to 13 loci18 to produce genome-wide data in the form of 6355 single nucleotide polymorphisms (SNPs) identified from 88 individual pink bollworm from seven wild populations in Australia, India, and Pakistan; and four laboratory colonies in the U.S. We used these data to assess the population structure of pink bollworm, with a particular focus on the Australian population. We also analysed data from Genbank for mtDNA COI for pink bollworm from six countries. Our results show minimal gene flow between Australia and the other populations that were sampled in this study, which reduces concerns about the threat of introductions of Bt-resistant pink bollworm from India and Pakistan.Here, we aimed to understand pink bollworm population structure by using a genotyping-by-sequencing technique (DArTseq)Pectinophora gossypiella; Entosol  Pty Ltd., NSW Australia). Fourth instar larvae were collected from fields of Bt cotton producing Cry1Ac + Cry2Ab (Bt toxins) in 2010 from the states of Telangana, Maharashtra, Karnataka, and Andhra Pradesh in India19, and from fields of Bt cotton producing Cry1Ac in 2016–2017 from the provinces of Punjab and Sindh in Pakistan.We analysed the genomes of 88 pink bollworm from Australia, India, Pakistan, and the U.S. Table . Male mo20. Both APHIS-S colonies were obtained from the United States Department of Agriculture (USDA) Animal and Plant Health Inspection Service (APHIS) laboratory in Phoenix, Arizona, where they had been maintained for over 40 years without exposure to Bt toxins or other insecticides22. Subsets of the APHIS-S colony were provided to the USDA Agricultural Research Service in Maricopa, Arizona in 2006 (APHIS-S_2) and 2018 (APHIS-S_1). Bt4R and Bt4-R2 are laboratory-selected resistant colonies: Bt4R was derived from the Bt-susceptible Western Cotton Research Laboratory (WCRL) colony from 2007 to 2008 by laboratory selection for Cry1Ac resistance23. Bt4-R2 was obtained from Bt4R in 2010 and has 28-fold resistance to Cry1Ac and > 10,000-fold resistance to Cry2Ab24. Larvae from all four colonies were reared in the laboratory on wheat germ diet25 at 26 °C and a photoperiod of 14 h light:10 h dark.For pink bollworm from the U.S., we used individuals from four laboratory colonies in Arizona: APHIS-S_1, APHIS-S_2, Bt4R, and Bt4-R2, where this pest was declared eradicated in 201826. Short-read sequences were then processed following the DArTseq bioinformatic pipeline to yield genotyping data in the form of SNPs26.We sent 90 pink bollworm samples to Diversity Arrays Technology  for DNA extraction, quantification, and genotyping , call rate (threshold: 0.95), and minor allele frequency (threshold: 0.02). The final filtered dataset contained 88 individual genotypes, 6355 SNP markers, and 1.41% missing data.We received genotyping outputs in the DarT ‘2 row’ format, where alleles are scored “0” for homozygous reference state, “1” for heterozygous, and “2” for homozygous alternate (or SNP) state31 to calculate observed (Ho) and expected (He) heterozygosity, as well as inbreeding coefficients  for each population from the filtered dataset.In R, we used ‘hierfstat’ version 0.5.1132. We randomly permuted the AMOVA output 1000 times to test if populations and colonies were significantly different using the function ‘randtest’ from the package ‘ade4’ version 1.7.1933. We then estimated pairwise genetic differentiation (FST) between populations and colonies using the function ‘genet.dist’ and method ‘WC84’ from the ‘hierfstat’ package, version 0.5.1135.We used R to analyse genetic variation between and within populations by performing an Analysis of Molecular Variance (AMOVA) with the ‘poppr’ package version 2.9.3Pectinophora scutigera; see Fig. We conducted a principal component analysis based on Euclidean genetic distances, using the function ‘glPCA’ implemented in the ‘adegenet’ package in R. We performed two analyses, one with only the 11 populations and colonies of pink bollworm, and another that also included an ‘outgroup’ population of spotted pink bollworm . A maximum likelihood (ML) phylogeny was constructed in Iqtree version 1.2.139 using the best-fit substitution model automatically selected by the software, with 10,000 bootstrap iterations to assess clade support. The resulting output was read into R using ‘ape’ version 5.6.240 for data visualisation.To examine relationships among samples in a phylogenetic context, we converted our SNP data to variant call format (VCF) using ‘radiator’ version 1.2.241. The nucleotide diversity of each population was then calculated using the ‘nuc.div’ function in R from the ‘pegas’ package version 1.142. COI sequences were converted to haplotypes using the same package, and the function ‘haploNet’ was used to construct a haplotype network.Finally, to further investigate genetic diversity and population structure of global pink bollworm populations, we obtained 31 mitochondrial COI sequences in FASTA format from GenBank Table  for popu9 = 4.87; P < 0.001). Mean Ho was significantly higher for the field populations from India and Pakistan (0.20) than for Australia (0.14) . Ho was not correlated with the number of field sites sampled per population across the seven field populations  nor the number of individuals sampled per population across all 11 populations and colonies .Observed heterozygosity (Ho) was low within each of the 11 populations and colonies studied  was higher for field populations (0.13) than laboratory colonies (0.03)   was significantly lower than expected heterozygosity (He) (mean = 0.18)  analysis of the filtered dataset (6355 SNPs) indicated an optimal K value of five clusters Fig. . We founWe identified 13 haplotypes from 31 COI sequences from GenBank, obtained from pink bollworm individuals in six countries: Australia , India (n = 12), Pakistan n = 5), the U.S. (n = 3), Israel (n = 4), and Kenya (n = 4). Nucleotide diversity was 0.002 in India (10 haplotypes), 0.0007 in Israel (two haplotypes), and 0 in the other four countries (one haplotype each)  was higher in the field populations. This was surprising as laboratory colonies are expected to show greater FIS because their smaller population sizes increase mating between related individuals47. However, a meta-analysis of self-incompatible plant species also found that FIS was positively correlated with population size48, which is similar to our findings. Estimates of diversity and FIS using SNP data may be influenced by missing data, rare alleles, sample size, and population structure49. However, in our study Ho was not correlated with the number of individuals nor the number of field sites sampled per population, and our SNP matrix had < 1.5% missing data. As noted by Schmidt et al.,49 more work is needed to evaluate the implications of differences between observed and expected heterozygosity50.Our results showed that genetic diversity based on heterozygosity at 6355 SNP markers and nucleotide diversity at mtDNA COI was low within all populations and colonies. As expected, heterozygosity was significantly lower within laboratory colonies from the U.S. compared to within field populations from Australia, India, and Pakistan. However, putative inbreeding 54. In such studies, the newly available reference genome for pink bollworm55 and wider geographic sampling could yield insights facilitating better monitoring and management of this cosmopolitan pest.Although pink bollworm is present in over 150 countries worldwide Fig. ”. Thus, Supplementary Information.